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Isa Danieli a Binario Rosa in una “passeggiata devota”

Isa Danieli a Binario Rosa in una “passeggiata devota”

Torna l’appuntamento con Binario Rosa, al Museo Nazionale Ferroviario di Pietrarsa, sabato 27 Luglio 2024 ore 21, che dopo il successo del one woman show di Giusy Freccia, vede protagonista Isa Danieli con lo spettacolo “Raccontami una passeggiata devota”.

Un percorso di donna e di attrice che ha attraversato e attraversa, i generi più diversi delle forme teatrali esistenti.
Dal gradino più basso, quello della sceneggiata, alla tragedia greca di Euripide e di Eschilo, fino ad incarnare le parole di autori contemporanei che hanno scritto per lei. Dalla Wertmuller a Chiti, da Ruccello a Santanelli e poi Moscato, Letizia Russo e Antonio Tarantino, fino al recente Ruggero Cappuccio.
Una tradizione teatrale antichissima, ”tradita” e amata al tempo stesso. Parole soffiate fino al cuore di chi ascolta, per trattenerle, perché rimbalzino in un’eco mai rassegnata e muta.

I prossimi appuntamenti di Binario Rosa:

1 Settembre 2024 ore 21
Marini Live
con Francesca Marini
(e la selezione musicale di Roberto Criscuolo)

15 Settembre 2024 ore 20
Medea
con Gina Perna
(con musiche dal vivo di Matteo Canonico)

28 Settembre 2024 ore 20
Poche Storie
con Gea Martire

La kermesse organizzata dall’associazione culturale M&N’s, con la direzione artistica di Nicola Le Donne, sarà un viaggio unico e personale, un’occasione per riflettere su tematiche attuali e universali attraverso la lente dell’esperienza e della sensibilità femminile. “Binario Rosa” non è solo teatro, ma anche un’occasione per valorizzare il talento e la creatività delle donne. Un modo per dare risalto alle loro voci e alle loro storie, spesso relegate ai margini. Un’iniziativa che si inserisce in un contesto sociale e culturale in cui la lotta per l’uguaglianza di genere è ancora più che mai attuale.
Gli spettacoli si terranno nell’Anfiteatro del Museo Nazionale Ferroviario di Pietrarsa. Biglietti disponibili presso il Museo oppure via WhatsApp ai numeri 3792377322 e via mail all’indirizzo info@mens-lab.i

CONCERTO A LUME DI CANDELA: LA GRANDE LIRICA ITALIANA A VILLA DOMI

CONCERTO A LUME DI CANDELA: LA GRANDE LIRICA ITALIANA A VILLA DOMI

Grande attesa per il Summer Night’s Opera Dream – Puccini & Co. a lume di candela, il grande evento dedicato alla musica classica e alla canzone napoletana d’autore.
Prodotto dalla “Fuori Campo Eventi” di Mirka Contessa, la serata organizzata nella suggestiva cornice di Villa Domi, sarà un viaggio musicale a lume di candela che spazia da Puccini a Verdi da Di Capua a Mozart.
La manifestazione sarà l’occasione per celebrare tutti insieme il 100° anniversario dalla morte del Maestro Giacomo Puccini e per festeggiare il riconoscimento dell’UNESCO della Pratica del Canto Lirico Italiano come Patrimonio Culturale immateriale dell’umanità.
Si ritroveranno sul palco tre grandi protagonisti della musica classica, reduci da grandi successi internazionali: il soprano Martina Bortolotti von Haderburg, il Baritono Luigi Cirillo, pupillo di Pavarotti. Entrambi i cantanti di fama internazionale hanno cantato in tutto il mondo in prestigiosi teatri tra cui il Teatro alla Scala, Gran Teatro La Fenice, Teatro dell’Opera di Roma, Opera del Cairo, Royal Opera House di Muscat, solo per citarne alcuni e si sono recentemente esibiti al Teatro San Carlo. Ad accompagnarli al pianoforte il Maestro Keith Goodman, Compositore, Direttore e Pianista italo-americano di fama .
Circondati dal panorama mozzafiato del Golfo di Napoli e del Vesuvio gli spettatori potranno ascoltare brani d’Opera e della Canzone Napoletana che hanno reso celebri i più grandi Cantanti del mondo.
Villa Domi è stata inoltre la residenza di una delle massime stelle dell’opera buffa napoletana e talentuosa pittrice, Celeste Coltellini, il cui spirito alleggia ancora tra le sale e i giardini, ispirando all’arte e all’armonia. Mentre risuonano ancora gli accordi dell’eccelso Mozart che pure passo per Villa Domi lasciandovi tracce del suo genio.
Per Info&Prenotazioni 0815922233 – 3274365398
NOTE BIOGRAFICHE SUGLI ARTISTI
Martina Bortolotti von Haderburg Soprano:
Il soprano internazionle Martina Bortolotti si è esibita in tutto il mondo, come a Washington DC per la Steinway Series, In Corea del Sud al Seoul Arts Center, in Tournée in Cina, in Europa e Oriente come al Royal Opera House di Muscat e all’Opera del Cairo. In Italia al Teatro alla Scala, al Gran Teatro La Fenice di Venezia e recentemente anche al Real Teatro di San Carlo di Napoli. Ha inciso prime mondiali per la NAXOS e partecipato anche al film “Un amore cosi grande” con Il VOLO. È stata insignita del Premio Internazionale “Books for Peace” presso la sede del Parlamento Europeo a Roma e di altri premi internazionali come “Voci nuove per Puccini”a Vienna. È docente di Canto e Arte Scenica presso l’Istituto di Alta Formazione Musicale “Claudio Monteverdi” di Bolzano.
Luigi Cirillo – Baritono
Ha intrapreso lo studio del canto presso il Conservatorio Statale di Musica di Salerno, sotto la guida della Sig.ra Rosetta Arena e del M° Carlo Tuand e successivamente con il tenore Nazzareno Antinori. Ha frequentato corsi di perfezionamento con Rolando Panerai, Gianni Raimondi, Fiorenza Cossotto, Gabriella Tucci, ed è stato anche allievo e pupillo del grande LUCIANO PAVAROTTI.
Nel 1999 vince il Concorso Mario Lanza ad Isernia, debuttando nel ruolo di Alfio nella Cavalleria Rusticana di P. Mascagni.
Nel 2008 canta in un concerto trasmesso in eurovisione per l’assegnazione del premio “Gigli d’Oro” presso il Teatro Persiani di Recanati, con il Tenore Andrea Bocelli.
Nel 2010 ha partecipato in qualità di baritono solista, alla realizzazione dei DVD di “Tosca” e de “La Fanciulla del West” di G. Puccini per la Fondazione Festival Pucciniano di Torre del Lago.
Nel 2012, in occasione dell’evento “Omaggio a Pavarotti” a Correggio (RE), è stato insignito del premio “Pavarotti d’Oro”.
Svolge un intensa attività concertistica ed operistica presso importanti teatri italiani: Teatro Municipale Giuseppe Verdi di Salerno, Teatro Regio di Parma, Teatro San Carlo di Napoli, Teatro alla Scala di Milano, Teatro Regio di Torino, Teatro dell’Opera di Roma, Fondazione Festival Pucciniano, Teatro Comunale Francesco Cilea di Reggio Calabria, Teatro Politeama di Catanzaro, Teatro Sferisterio di Macerata, Teatro Alfonso Rendano di Cosenza, Teatro Ventidio Basso di Ascoli Piceno, Teatro Comunale di Mantova; interpretando ruoli nelle seguenti opere liriche: “Nabucco”, “L’elisir d’amore”, “Cavalleria Rusticana”, “La Traviata”, “Rigoletto”, “Un ballo in maschera”, “Macbeth”, “Aida”, “Otello”, “Il Trovatore”, “Il barbiere di Siviglia”, “Madama Butterfly”, “Tosca”, “Turandot”, “Carmen”, “Le nozze di Figaro”, “La forza del destino”, “La Fanciulla del West”, “Don Pasquale”, “La Bohéme”, “Gianni Schicchi”, “Falstaff”.
Ha cantato sotto la direzione di illustri maestri, come Janos Acs, Nicola Luisotti, Zubin Mehta, Miguel Roa, Riccardo Frizza, Valery Gergiev, Evelino Pidò, Guillaime Tourniaire, Tadeusz Serafin, Gabriele Ferro, Carlo Palleschi, Giuseppe Acquaviva, Alberto Veronesi, Pier Giorgio Morandi, Fabio Mastrangelo, Jordi Bernàcer, Daniel Oren, Pinchas Steinberg; e di insigni registi come Riccardo Canessa, Henning Brockhaus, Giulio Ciabatti, Mario Corradi, Eike Gramss, Daniele Abbado, Jorge Lavelli, Beppe De Tomasi, Kirsten Harms, Pippo Del Bono
Keith Goodman Musicista italoamericano
ha studiato presso il Conservatorio San Pietro a Majella di Napoli, dove si diploma in: Pianoforte, Composizione, Direzione d’orchestra, Strumentazione per banda, Musica Corale. È autore di numerose composizioni premiate ed eseguite in varie manifestazioni. Svolge attività concertistica in Italia e all’estero. (Spagna, Portogallo, Slovenia, Ungheria, Cina) Dal 2009 è direttore stabile e fondatore dell’Orchestra San Giovanni, dal 2013 del coro Vox Artis e nel 2018/19 è stato direttore dell’orchestra dell’Università Parthenope di Napoli. Ha al suo attivo pubblicazioni discografiche ed editoriali. Ha collaborato con Radio Vaticana alla realizzazione di trasmissioni musicali.

Germano Bellavia:”Se fosse stato per me avrei fatto solo l’ultrà del Napoli.”

Di Massimo Sparnelli

Un grande tifoso degli azzurri, sia da tifoso che da dirigente ho visto Germano in tutti gli stadi del mondo, anche da solo, per seguire il suo amato Napoli.

“Da bambino ho vissuto a New York per un po’ perché mia madre mi mandò da mio zio Raffaele a Little Italy per imparare l’inglese. Quando tornai parlavo più napoletano di prima: inglese zero.
La mia carriera di attore iniziò grazie a Nanni Loy che mi scelse per Scugnizzi, il musical nel 1987, avevo 17 anni. Non avrei mai fatto l’attore perché mi bastava fare il pasticciere. A fare l’attore ci pensava mio fratello Antonio, allievo di Gigi Proietti. Antonio frequentava il laboratorio di esercitazioni sceniche e aveva formato una compagna di 13 attori (tutti allievi di Proietti) a Latina e viveva lì. Quando feci questo provino ero al liceo, lui stava parlando con mia madre e mi feci passare il telefono e gli dissi che Nanny Loy mi aveva scelto per il musical. Antonio iniziò ad urlare come un pazzo dalla felicità. E’ fu l’ultima che lo sentii. Se c’è un motivo per cui faccio l’attore e’ perché ho tentato di fare quello che mio fratello Antonio, buonanima, non è riuscito a fare, altrimenti avrei fatto solo il pasticciere. La mia psicologa dice che faccio il pasticcere per la famiglia, l’attore per mio fratello Antonio e che se fosse stato per me “Da bambino ho vissuto a New York per un po’ perché mia madre mi mandò da mio zio Raffaele a Little Italy per imparare l’inglese. Quando tornai parlavo più napoletano di prima: inglese zero.
La mia carriera di attore iniziò grazie a Nanni Loy che mi scelse per Scugnizzi, il musical nel 1987, avevo 17 anni. Non avrei mai fatto l’attore perché mi bastava fare il pasticciere. A fare l’attore ci pensava mio fratello Antonio, allievo di Gigi Proietti. Antonio frequentava il laboratorio di esercitazioni sceniche e aveva formato una compagna di 13 attori (tutti allievi di Proietti) a Latina e viveva lì. Quando feci questo provino ero al liceo, lui stava parlando con mia madre e mi feci passare il telefono e gli dissi che Nanny Loy mi aveva scelto per il musical. Antonio iniziò ad urlare come un pazzo dalla felicità. E’ fu l’ultima che lo sentii. Se c’è un motivo per cui faccio l’attore e’ perché ho tentato di fare quello che mio fratello Antonio, buonanima, non è riuscito a fare, altrimenti avrei fatto solo il pasticciere. La mia psicologa dice che faccio il pasticcere per la famiglia, l’attore per mio fratello Antonio e che se fosse stato per me avrei fatto solo l’ultrà del Napoli.”

PREMIO ELSA MORANTE, SEZIONE POESIE, PRIMO VINCITORE DEL PREMIO FRANCESCO TERRONE

Nell’ambito del Premio Procida Isola di Arturo Elsa Morante XXXVII edizione, il giorno 19 luglio alle 19.30, a piazza Marina Grande verrà assegnato il premio per la sezione Poesia all’ing. Francesco Terrone, poeta e scrittore di successo, con la sua opera “L’urlo dell’innocenza”.
La serata, presentata da Noemi Maria Cognini, in arte Gherrero, vedrà protagonisti Francesco Terrone, ma anche il Prof.re Carlo Di Lieto, docente di Letteratura italiana presso l’Università Suor Orsola Benincasa di Napoli, che ci introdurrà all’essenza stessa dell’arte poetica terroniana.
La serata sarà allietata magicamente da “I solisti dell’Orchestra Sinfonica Nazionale del Cinema” diretti dal M° Raffaele Iannicelli con la partecipazione della soprano Rossana Potenza e la special guest, il maestro Carmine Padula. Le musiche faranno da accompagnamento all’interpretazione delle liriche di Francesco Terrone da parte di Antonio Speranza.
Sarà una serata all’insegna della cultura e dell’arte con momenti che, senza alcun dubbio, accarezzeranno il cuore di emozioni.
L’assessore Michele Assante del Leccese DICHIARA:

Siamo onorati di ospitare un’orchestra così importante e di consegnare al maestro Terrone il premio per la sezione poesia per il Premio Procida Isola di Arturo Elsa Morante

AMICHEVOLI ESTIVE DEL NAPOLI IN ESCLUSIVA SU ONEFOOTBALL

Per la prima volta i tifosi del Napoli potranno assistere in diretta alle partite amichevoli estive da ogni parte del mondo e su qualsiasi dispositivo mobile, da pc, tablet e su Smart Tv.

All’interno della piattaforma di OneFootball i tifosi azzurri potranno vedere gratuitamente la prima partita contro l’Anaune Val di Non e acquistare il Napoli Summer Pass che include le altre quattro gare a pagamento. Oltre alle gare amichevoli saranno trasmesse in diretta e gratuitamente anche le conferenze stampa del Club, contenuti speciali, dietro le quinte, interviste esclusive e gli highlights delle partite.

COME SEGUIRE IN LIVE STREAMING IL NAPOLI

A partire da Venerdì 12 Luglio e fino alle 23:59 di Venerdì 19 Luglio sarà possibile acquistare il Napoli Summer Pass, che darà accesso a tutte le amichevoli estive che si giocheranno nei ritiri a Dimaro e a Castel di Sangro.

Il Napoli Summer Pass, al prezzo di 14,99€, include l’accesso a tutte e quattro le amichevoli estive a pagamento, garantendo un risparmio del 35% rispetto all’acquisto complessivo delle singole gare.

Ecco l’elenco delle gare incluse con il Napoli Summer Pass:

PARTITA DATA
Napoli vs Anaune Val di Non* 16/07/2024 h 18:00
Napoli vs Mantova 20/07/2024 h 18:00
Napoli vs Adana Demirspor 28/07/2024 h 20:00
Napoli vs Brest 31/07/2024 h 20:00
Napoli vs Girona 03/08/2024 h 18:30

*Gara visibile a tutti gratuitamente.

Da Sabato 20 Luglio sarà possibile acquistare le singole partite in pay-per-view, iniziando da Napoli vs Mantova. I prezzi delle singole partite saranno i seguenti:

  • Napoli vs Mantova: 1,99€
  • Napoli vs Adana Demirspor: 6,99€
  • Napoli vs Brest: 6,99€
  • Napoli vs Girona: 6,99€

Per poter acquistare e guardare le partite amichevoli a pagamento in diretta sarà in ogni caso necessario prima accedere e registrarsi alla piattaforma di OneFootball via Web o su App Mobile.

COME ACQUISTARE IL NAPOLI SUMMER PASS

Per acquistare il Napoli Summer Pass sarà necessario:

  1. Registrarsi alla piattaforma di OneFootball via Web o su App Mobile
  2. Digitare sulla barra di ricerca “Napoli” e accedere al profilo del Club su OneFootball
  3. Selezionare la sezione “Partite”, cliccare su una delle prossime gare amichevoli a pagamento
  4. Completare l’acquisto al prezzo di € 14,99 del Napoli Summer Pass

Una volta acquistato il Napoli Summer Pass sarà possibile seguire la diretta live delle amichevoli estive con le seguenti modalità:

In caso di necessità di assistenza relativa all’acquisto delle partite clicca qui

Sarà un’estate di emozioni da non perdere, Napoli e OneFootball sono pronti ad accompagnarti ovunque tu sia. Basta solo uno smartphone, l’app di OneFootball e la passione del vero tifoso azzurro.

Anytime, Anywhere, Proud To Be Napoli.

Premio Procida Isola di Arturo Elsa Morante I Finalisti

Il “Premio Procida-Isola di Arturo-Elsa Morante”, nato nel 1986 a pochi mesi dalla scomparsa della scrittrice, primo in Italia dedicato alla figura di Elsa Morante giunge quest’anno alla sua XXXVII edizione. La giuria tecnica del Premio, sezione Narrativa, presieduta da Silvia Zoppi Garampi e composta da Antonio Corsaro, Alberto Fraccacreta, Massimo Onofri e Ilaria Tufano, ha selezionato la seguente terna finalista:

Adriàn N. Bravi, Adelaida (Nutrimenti 2024)
Antonio Franchini, Il fuoco che ti porti dentro (Marsilio 2024)
Federica Manzon, Alma (Feltrinelli 2024)

“I libri saranno adesso acquistati dal Comune di Procida e letti e votati dalla Giuria dei Lettori. La serata finale ci sarà l’urna con tutti i voti e la lavagna di ardesia (come nella famosa foto di El-sa Morante che indica il suo libro vincitore allo Strega) dove verranno segnati i voti man mano che lo spoglio andrà avanti. Il vincitore sarà così scelto dai Lettori, veri giudici supremi che de-cretano il successo o meno di qualunque opera letteraria. La cerimonia di premiazione avrà luo-go a Procida il 28 settembre 2024 in piazza Marina Grande. Quest’anno infatti il premio si leghe-rà, con una sezione speciale, alla Procida Vela Cup (evento nazionale per la prima volta sulla no-stra isola) e sarà gemellato anche con il Premio Nazionale Sergio Staino, nato in onore del gran-de artista scomparso il 21 ottobre 2023 che era stato ospite con un incontro e una mostra a Pro-cida durante l’anno della Capitale. I vincitori delle altre sezioni saranno poi resi noti durante l’anno.” ha dichiarato soddisfatto il Delegato alla Cultura Michele Assante del Leccese.

Grazie, De Laurentiis…………..

“Preside’ caccia ‘e sord!”. Questa frase ha rappresentato uno slogan per anni dell’ambiente azzurro. Una esortazione, quasi intimidatoria, dei tifosi verso Aurelio De Laurentiis, presunto colpevole di lesinare sugli investimenti. Una austerità che in realtà è stata sempre solo millantata e mai reale, una illazione che si infrange su quasi due decenni di presidenza. Ed infatti oggi quell’urlo divenuto luogo comune, suona come profezia perché in questo momento storico del calcio nostrano l’unico che spende e “caccia i soldi” è solo Adl. Un Presidente che, attraverso la sua gestione virtuosa e lungimirante, si è messo nelle condizioni di avere una delle rare Società non solo in Italia, ma in Europa, in grado di poter vantare una economia florida ed una capacità di investimento che nella nostra Nazione non possono evidenziare neppure i cosiddetti “Top Club”, meglio definite da Antonio Conte “le solite note”, ovvero le nobili squadre del profondo Nord. Inter, Milan e Juventus sono alle prese con le forche caudine del risparmio e della ricapitalizzazione per poter essere competitive sul mercato. Un processo che, se tutto andasse bene (per loro), ha bisogno di anni per potersi compiere.

Oggi invece il Napoli è padrone delle proprie azioni, sia economiche che umane, è svincolato da qualsiasi fondo esoso, scevro da obblighi vincolanti e in pieno possesso di quel “tesoretto” frutto del lavoro certosino e imprenditoriale avviato, condotto e coronato da De Laurentiis. Don Aurelio ha sorpreso tutti e si è di nuovo imposto, dopo una stagione sciagurata, con un rilancio che ha strabiliato anche i più ottimisti. Persino il sottoscritto, che è venuto a conoscenza in tempo quasi reale della trattativa con Antonio Conte, ha dovuto registrare testimonianze di scetticismo diffuso e generale. E invece Adl, da autentico mattatore, ha assestato il suo ennesimo colpo di teatro. “Con te partirò” non è solo la celeberrima canzone di Andrea Bocelli, bensì il nuovo claim del Napoli che inizia la stagione della riscossa dal suo sergente di ferro, un uomo verticale e intransigente che ha già dettato il suo nuovo ordine etico e calcistico.

“Preside’ caccia ‘e sord” non è più un imperativo ma un dato di fatto. Un ingaggio formidabile per il tecnico di cui il nostro ambiente aveva assoluto bisogno, ed acquisti già centrati in attesa di nuovi sviluppi. Con una sola certezza: l’orizzonte è sempre più azzurro. Grazie a Don Aurelio, il Presidente del presente e del futuro…

Artificial Intelligence in Healthcare: Role of AI in Healthcare

AI in health care: the risks and benefits

importance of ai in healthcare

Artificial intelligence is being used in healthcare for everything from answering patient questions to assisting with surgeries and developing new pharmaceuticals. Documentation gaps can lead to inaccurate coding that may diminish revenue and slow the reimbursement process or stop it altogether. The company’s motion stabilizer system is intended to improve performance and precision during surgical procedures. Its MUSA surgical robot, developed by engineers and surgeons, can be controlled via joysticks for performing microsurgery.

However, the most significant increase in published articles occurred in the past three years (please see Fig. 2). Finally, the collaboration index (CI), which was calculated as the total number of authors of multi-authored articles/total number of multi-authored articles, was 3.97 [46]. In this article, I will look at how it may have more of an impact on the healthcare industry than initially meets the eye and what facets of the sector AI can revolutionize. The WHO report also provides recommendations that ensure governing AI for healthcare both maximizes the technology’s promise and holds healthcare workers accountable and responsive to the communities and people they work with.

This includes processing and analyzing clinical trials to find the effects of vaccines, drugs, and other treatments as well as tracing the origins of virus strains. One of the most interesting uses of AI in healthcare now is the integration of biotech platforms. Machine learning is being used by several pharmaceutical companies, including Pfizer, to find immuno-oncology treatments. They are attempting to identify new combinations of medicinal ingredients for creating novel pharmaceuticals by looking for trends in medical data and examining the effects of current medications on patients.

Their bibliometric analysis demonstrates how robotic-assisted surgery has gained acceptance in different medical fields, such as urological, colorectal, cardiothoracic, orthopaedic, maxillofacial and neurosurgery applications. Additionally, the bibliometric analysis of Guo et al. [25] provides an in-depth study of AI publications through December 2019. The paper focuses on tangible AI health applications, giving researchers an idea of how algorithms can help doctors and nurses.

Overall, the use of AI in TDM has the potential to improve patient outcomes, reduce healthcare costs, and enhance the accuracy and efficiency of drug dosing. As this technology continues to evolve, AI will likely play an increasingly important role in the field of TDM. AI in healthcare is expected to play a major role in redefining the way we process healthcare data, diagnose diseases, develop treatments and even prevent them altogether. By using artificial intelligence in healthcare, medical professionals can make more informed decisions based on more accurate information – saving time, reducing costs and improving medical records management overall. From identifying new cancer treatments to improving patient experiences, AI in healthcare promises to be a game changer – leading the way towards a future where patients receive quality care and treatment faster and more accurately than ever before.

As healthcare enters the era of AI and more possibilities emerge, organizations everywhere should be more motivated than ever to work with healthcare providers who improve patients’ lives. For example, these AI systems can be invaluable in tracking health metrics and detecting any abnormal changes in real time for patients with chronic conditions like diabetes or heart disease. When the AI system detects concerning patterns, like fluctuations in heart rate or blood glucose levels, it can alert physicians or home caretakers to take preventative action. IBM watsonx Assistant is built on deep learning, machine learning and natural language processing (NLP) models to understand questions, search for the best answers and complete transactions using conversational AI. Are you looking to extract actionable insights from your data using the latest artificial intelligence technology? See how ForeSee Medical can empower you with insightful HCC risk adjustment coding support and integrate it seamlessly with your electronic health records.

If we consider the second block, the red one, three different clusters highlight separate aspects of the topic. Through AI applications, it is possible to obtain a predictive approach that can ensure that patients are better monitored. This also allows a better understanding of risk perception for doctors and medical researchers. In the second cluster, the most frequent words are decisions, information system, and support system. This means that AI applications can support doctors and medical researchers in decision-making. Information coming from AI technologies can be used to consider difficult problems and support a more straightforward and rapid decision-making process.

The joint center is building an infrastructure that supports research in areas such as genomics, chemical and drug discovery and population health. The collaboration employs big data medical research for the purpose of innovating patient care and approaches to public health threats. The primary goal of BenevolentAI is to get the right treatment to the right patients at the right time by using AI to produce a better target selection and provide previously undiscovered insights through deep learning. BenevolentAI works with major pharmaceutical groups to license drugs, while also partnering with charities to develop easily transportable medicines for rare diseases. Valo uses artificial intelligence to achieve its mission of transforming the drug discovery and development process. With its Opal Computational Platform, Valo collects human-centric data to identify common diseases among a specific phenotype, genotype and other links, which eliminates the need for animal testing.

The projected benefits of using AI in clinical laboratories include but are not limited to, increased efficacy and precision. Automated techniques in blood cultures, susceptibility testing, and molecular platforms have become standard in numerous laboratories globally, contributing significantly to laboratory efficiency [21, 25]. Automation and AI have substantially improved laboratory efficiency in areas like blood cultures, susceptibility testing, and molecular platforms. This allows for a result within the first 24 to 48 h, facilitating the selection of suitable antibiotic treatment for patients with positive blood cultures [21, 26]. Consequently, incorporating AI in clinical microbiology laboratories can assist in choosing appropriate antibiotic treatment regimens, a critical factor in achieving high cure rates for various infectious diseases [21, 26]. AI applications will continue to help streamline various tasks, from answering phones to analyzing population health trends (and, likely, applications yet to be considered).

The real turning point, however, came with the realization of how AI could address some of the most pressing challenges in healthcare, ranging from diagnostic accuracy to personalized treatment and operational efficiency. Several authors have analysed AI in the healthcare research stream, but in this case, the authors focus on other literature that includes business and decision-making processes. On the one hand, some contributions belong to the positivist literature and embrace future applications and implications of technology for health service management, data analysis and diagnostics [6, 80, 88]. On the other hand, some investigations also aim to understand the darker sides of technology and its impact. For example, as Carter [89] states, the impact of AI is multi-sectoral; its development, however, calls for action to protect personal data.

Global strategy on digital health 2020-2025

Additionally, data mining and big data are a step forward in implementing exciting AI applications. According to our specific interest, if we applied AI in healthcare, we would achieve technological applications to help and support doctors and medical researchers in decision-making. The link between AI and decision-making is the reason why we find, in the seventh position, the keyword clinical decision support system. AI techniques can unlock clinically relevant information hidden in the massive amount of data that can assist clinical decision-making [64].

Since AI will be learning from older systems and data, it is not an impossibility that such discrimination may occur. As is always the case when we stumble upon discoveries and inventions, the one thing that we must keep top of mind is how organizations can adapt and the potential for growth and change. When it comes to AI, the possibilities are seemingly endless, and this is true for the healthcare industry. 8 min read – By using AI in your talent acquisition process, you can reduce time-to-hire, improve candidate quality, and increase inclusion and diversity.

importance of ai in healthcare

An AI system will do this same process, in a fraction amount of time and have greater accuracy because it can tap into multiple databases at once. Collaboration among stakeholders is vital for robust AI systems, ethical guidelines, and patient and provider trust. Continued research, innovation, and interdisciplinary collaboration are important to unlock the full potential of AI in healthcare. With successful integration, AI is anticipated to revolutionize healthcare, leading to improved patient outcomes, enhanced efficiency, and better access to personalized treatment and quality care. From scheduling appointments to processing insurance claims, AI automation reduces administrative burdens, allowing healthcare providers to focus more on patient care.

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Finally, although bibliometric analysis has limited the subjectivity of the analysis [15], the verification of recurring themes could lead to different results by indicating areas of significant interest not listed here. Finally, health care providers must be vigilant about detecting and preventing attacks on the AI algorithms themselves. Health care providers should consider being transparent about the algorithms they are using and the data they are collecting. Doing so can reduce the risk of algorithmic bias while ensuring that patients understand how their data is being used.

Table 9 represents the number of citations from other articles within the top 20 rankings. For instance, Burke et al. [67] writes the most cited paper and analyses efficient nurse rostering methodologies. Immediately thereafter, Ahmed M.A.’s article proposes a data-driven optimisation methodology to determine the optimal number of healthcare staff to optimise patients’ productivity [68]. Finally, the third most cited article lays the groundwork for developing deep learning by considering diverse health and administrative information [51]. In order to effectively train Machine Learning and use AI in healthcare, massive amounts of data must be gathered. Acquiring this data, however, comes at the cost of patient privacy in most cases and is not well received publicly.

However, there are few controversies such as increased chances of data breaches, concern for clinical implementation, and potential healthcare dilemmas. In this article, the positive and negative aspects of AI implementation in healthcare are discussed, as well as recommended some potential solutions to the potential issues at hand. Public perception of the benefits and risks of AI in healthcare systems is a crucial factor in determining its adoption and integration. In medicine, patients often trust medical staff unconditionally and believe that their illness will be cured due to a medical phenomenon known as the placebo effect. In other words, patient-physician trust is vital in improving patient care and the effectiveness of their treatment [105]. For the relationship between patients and an AI-based healthcare delivery system to succeed, building a relationship based on trust is imperative [106].

According to Jiang et al. [64], AI can help physicians make better clinical decisions or even replace human judgement in healthcare-specific functional areas. According to Bennett and Hauser [80], algorithms can benefit clinical decisions by accelerating the process and the amount of care provided, positively impacting the cost of health services. Therefore, AI technologies can support medical professionals in their activities and simplify their jobs [4]. Finally, as Redondo and Sandoval [81] find, algorithmic platforms can provide virtual assistance to help doctors understand the semantics of language and learning to solve business process queries as a human being would. The use of AI technologies has been explored for use in the diagnosis and prognosis of Alzheimer’s disease (AD). AI-powered chatbots are being implemented in various healthcare contexts, such as diet recommendations [95, 96], smoking cessation, and cognitive-behavioral therapy [97].

This capability was instrumental in diagnosing diseases, predicting outcomes, and recommending treatments. For instance, AI algorithms can analyze medical images, such as X-rays and MRIs, with greater accuracy and speed than human radiologists, often detecting diseases such as cancer at earlier stages. Natural language processing is proving to be an invaluable tool in healthcare – allowing medical professionals to use artificial intelligence to more accurately diagnose illnesses and provide better personalized treatments for their patients.

Growing Evidence Shows Importance of AI for Healthcare – Center for Data Innovation

Growing Evidence Shows Importance of AI for Healthcare.

Posted: Thu, 25 Apr 2024 07:00:00 GMT [source]

Butterfly Network designs AI-powered probes that connect to a mobile phone, so healthcare personnel can conduct ultrasounds in a range of settings. Both the iQ3 and IQ+ products provide high-quality images and extract data for fast assessments. With the ability to create and analyze 3D visualizations, Butterfly Network’s tools can be used for anesthesiology, primary care, emergency medicine and other areas.

The risk of misdiagnosing patients is one of the most critical problems affecting medical practitioners and healthcare systems. A study found that diagnostic errors, particularly in patients who visit the ED, directly contribute to a greater mortality rate and a more extended hospital stay [32]. Fortunately, AI can assist in the early detection of patients with life-threatening diseases and promptly alert clinicians so the patients can receive immediate attention. Lastly, AI can help optimize health care sources in the ED by predicting patient demand, optimizing therapy selection (medication, dose, route of administration, and urgency of intervention), and suggesting emergency department length of stay. By analyzing patient-specific data, AI systems can offer insights into optimal therapy selection, improving efficiency and reducing overcrowding.

Both journals deal with cloud computing, machine learning, and AI as a disruptive healthcare paradigm based on recent publications. The IEEE Journal of Biomedical and Health Informatics investigates technologies in health care, life sciences, and biomedicine applications from a broad perspective. The next journal, Decision Support Systems, aims to analyse how these technologies support decision-making from a multi-disciplinary view, considering business and management. Therefore, the analysis of the journals revealed that we are dealing with an interdisciplinary research field. This conclusion is confirmed, for example, by the presence of purely medical journals, journals dedicated to the technological growth of healthcare, and journals with a long-term perspective such as futures. As stated by the methodological paper, the first step is research question identification.

Generative AI and Emerging Technology Forum

This journey of AI from a novel concept to a fundamental aspect of healthcare exemplifies a technological revolution, with the promise of better health outcomes for all. Data privacy is particularly important as AI systems collect large amounts of personal health information which could be misused if not handled correctly. Additionally, proper security measures must be put into place in order to protect sensitive patient data from being exploited for malicious purposes. “Consider all the vast amounts of data that AI has the potential to harness — from genomic, biomarker and phenotype data to health records and delivery systems. The technology is already being used to support decisions made in data-intensive specialties like radiology, pathology and ophthalmology,” according to HIMSS.

AiCure helps healthcare teams ensure patients are following drug dosage instructions during clinical trials. Supplementing AI and machine learning with computer vision, the company’s mobile app tracks when patients aren’t taking their medications and gives clinical teams time to intervene. In addition, AiCure provides a platform that gleans insights from clinical data to explain patient behavior, so teams can study how patients react to medications. Flatiron Health is a cloud-based SaaS company specializing in cancer care, offering oncology software that connects cancer centers nationwide to improve treatments and accelerate research. Using advanced technology, including artificial intelligence, it advances oncology by connecting community oncologists, academics, hospitals and life science researchers, providing integrated patient population data and business intelligence analytics. By leveraging billions of data points from cancer patients, Flatiron Health enables stakeholders to gain new insights and enhance patient care.

With this training, AI can identify abnormalities, such as tumors, infections or fractures. However, more data are emerging for the application of AI in diagnosing different Chat PG diseases, such as cancer. A study was published in the UK where authors input a large dataset of mammograms into an AI system for breast cancer diagnosis.

In this sense, Choudhury and Asan’s [26] scientific contribution provides a systematic review of the AI literature to identify health risks for patients. They report on 53 studies involving technology for clinical alerts, clinical reports, and drug safety. Considering the considerable interest within this research stream, this analysis differs from the current literature for several reasons. It aims to provide in-depth discussion, considering mainly the business, management, and accounting fields and not dealing only with medical and health profession publications. It focuses on health services management, predictive medicine, patient data and diagnostics, and clinical decision-making.

AI-driven predictive analytics can enhance the accuracy, efficiency, and cost-effectiveness of disease diagnosis and clinical laboratory testing. Additionally, AI can aid in population health management and guideline establishment, providing real-time, accurate information and optimizing medication choices. Integrating AI in virtual health and mental health support has shown promise in improving patient care.

For example, the g-index indicates an author’s impact on citations, considering that a single article can generate these. Table 2 indicates the currently known literature elements, uniquely identifying the research focus, motivations and research strategy adopted and the results providing a link with the following importance of ai in healthcare points. Additionally, to strengthen the analysis, our investigation benefits from the PRISMA statement methodological article [37]. Although the SLR is a validated method for systematic reviews and meta-analyses, we believe that the workflow provided may benefit the replicability of the results [37,38,39,40].

Greenlight Guru, a medical technology company, uses AI in its search engine to detect and assess security risks in network devices. The company specializes in developing medical software, and its search engine leverages machine learning to aggregate and process industry data. Meanwhile, its risk management platform provides auto-calculated risk assessments, among other services. Augmedix offers a suite of AI-enabled medical documentation tools for hospitals, health systems, individual physicians and group practices. The company’s products use natural language processing and automated speech recognition to save users time, increase productivity and improve patient satisfaction.

The H-index was introduced in the literature as a metric for the objective comparison of scientific results and depended on the number of publications and their impact [59]. For the practical interpretation of the data, the authors considered data published by the London School of Economics [60]. In the social sciences, the analysis shows values of 7.6 for economic publications by professors and researchers who had been active for several years. Therefore, the youthfulness of the research area has attracted young researchers and professors. At the same time, new indicators have emerged over the years to diversify the logic of the h-index.

The company’s platform has a variety of applications, including cancer research, cell therapy and developmental biology. The company’s AI-enabled digital care platform measures and analyzes atherosclerosis, which is a buildup of plaque in the heart’s arteries. The technology is able to determine an individual’s risk of having a heart attack and recommend a personalized treatment plan. Biofourmis connects patients and health professionals with its cloud-based platform to support home-based care and recovery.

It was found that ANN was better and could more accurately classify diabetes and cardiovascular disease. An article by Jiang, et al. (2017) demonstrated that there are several types of AI techniques that have been used for a variety of different diseases, such as support vector machines, neural networks, and decision trees. Each of these techniques is described as having a “training goal” so “classifications agree with the outcomes as much as possible…”.

AI can optimize health care by improving the accuracy and efficiency of predictive models and automating certain tasks in population health management [62]. However, successfully implementing predictive analytics requires high-quality data, advanced technology, and human oversight to ensure appropriate and effective interventions for patients. Furthermore, a study utilized deep learning to detect skin cancer which showed that an AI using CNN accurately diagnosed melanoma cases compared to dermatologists and recommended treatment options [13, 14]. Researchers utilized AI technology in many other disease states, such as detecting diabetic retinopathy [15] and EKG abnormality and predicting risk factors for cardiovascular diseases [16, 17].

PV demands significant effort and diligence from pharma producers because it’s performed from the clinical trials phase all the way through the drug’s lifetime availability. Selta Square uses a combination of AI and automation to make the PV process faster and more accurate, which helps make medicines safer for people worldwide. One use case example is out of the University of Hawaii, where a research team found that deploying deep learning AI technology can improve breast cancer risk prediction. More research is needed, but the lead researcher pointed out that an AI algorithm can be trained on a much larger set of images than a radiologist—as many as a million or more radiology images.

The rise of AI in healthcare has been a gradual but steady journey, catalyzed by technological advancements and the increasing demand for improved healthcare delivery. The integration of AI into the medical field has brought about a paradigm shift, making healthcare more efficient, accurate, and personalized. As AI technology continues to evolve, its role in healthcare is set to become even more significant, further solidifying its status as an indispensable tool in modern medicine.

Coli, etc., at a far faster rate than they could with manual scanning thanks to AI enhanced microscopes. A number of healthcare companies have turned to AI in healthcare to stop the loss of data. They can now segment and connect the necessary data using AI, which used to take years to handle.

  • For example, the company used AI and machine learning to support the development of a Covid-19 treatment called PAXLOVID.
  • The company generates phenotypic cellular data and gathers clinical data from human cohorts for deep learning and machine learning models to comb through.
  • Artificial Intelligence in healthcare is changing many of the administrative aspects of medical care.
  • Beyond concerns about the effectiveness of AI, there are also concerns about the potential for bias in the underlying algorithms.

AI techniques are an essential instrument for studying data and the extraction of medical insight, and they may assist medical researchers in their practices. The current abundance of evidence makes it easier to provide a broad view of patient health; doctors should have access to the correct details at the right time and location to provide the proper treatment [92]. Emergency department providers understand that integrating AI into their work processes is necessary for solving these problems by enhancing efficiency, and accuracy, and improving patient outcomes [28, 29]. Additionally, there may be a chance for algorithm support and automated decision-making to optimize ED flow measurements and resource allocation [30]. AI algorithms can analyze patient data to assist with triaging patients based on urgency; this helps prioritize high-risk cases, reducing waiting times and improving patient flow [31].

For example, algorithms can monitor patients’ vital signs, such as heart rate and blood pressure, and alert doctors if there is a sudden change. This can help health care providers respond quickly to potential emergencies and prevent serious health problems from developing. Access to these tools can also assist physicians in identifying treatment protocols, clinical tools, and appropriate drugs more efficiently. Providers https://chat.openai.com/ are also taking advantage of AI to document patient encounters in near real-time. Not only does this improve the documentation, but it can increase efficiency and reduce provider frustration with the time-consuming documentation tasks. Not surprisingly, some hospitals and providers also are using AI tools to verify health insurance coverage and prior authorization of procedures, which can reduce unpaid claims.

AI would propose a new support system to assist practical decision-making tools for healthcare providers. In recent years, healthcare institutions have provided a greater leveraging capacity of utilizing automation-enabled technologies to boost workflow effectiveness and reduce costs while promoting patient safety, accuracy, and efficiency [77]. By introducing advanced technologies like NLP, ML, and data analytics, AI can significantly provide real-time, accurate, and up-to-date information for practitioners at the hospital. According to the McKinsey Global Institute, ML and AI in the pharmaceutical sector have the potential to contribute approximately $100 billion annually to the US healthcare system [78]. Researchers claim that these technologies enhance decision-making, maximize creativity, increase the effectiveness of research and clinical trials, and produce new tools that benefit healthcare providers, patients, insurers, and regulators [78]. Using automated response systems, AI-powered virtual assistants can handle common questions and provide detailed medical information to healthcare providers [79].

By compiling and analyzing this data, Corti can deliver insights to help teams pinpoint inefficiencies, offer employees tailored feedback and update any call guidelines as needed. Healthee uses AI to power its employee benefits app, which businesses rely on to help their team members effectively navigate the coverage and medical treatment options available to them. It includes a virtual healthcare assistant known as Zoe that offers Healthee users personalized answers to benefits-related questions. Robots are being employed to gather, re-format, store, and trace data to make information access quicker and more reliable. Reputable IoT solution companies have been working closely with hospitals and other healthcare organizations to develop tools that combine strong AI.

Because AI can identify meaningful relationships in raw data, it can support diagnostic, treatment and prediction outcomes in many medical situations [64]. Additionally, predictions are possible for identifying risk factors and drivers for each patient to help target healthcare interventions for better outcomes [3]. AI techniques can also help design and develop new drugs, monitor patients and personalise patient treatment plans [78].

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It can be argued that this may not necessarily be true due to unrealistic expectations, but it is still a stigma that can cause uproar in the workplace. Like with applications in other industries, AI can also be used to assist human specialists with menial tasks to bolster productivity at healthcare institutions. By infusing computer vision and edge devices into the reconciliation process, AI can automate the manual process of identifying and counting the inventory in a surgical tray.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Healthcare facilities’ resources are finite, so help isn’t always available instantaneously or 24/7—and even slight delays can create frustration and feelings of isolation or cause certain conditions to worsen. The Robotics Institute at Carnegie Mellon University developed HeartLander, a miniature mobile robot designed to facilitate therapy on the heart. Under a physician’s control, the tiny robot enters the chest through a small incision, navigates to certain locations of the heart by itself, adheres to the surface of the heart and administers therapy.

A study suggests that,The software can identify colorectal cancer photos, which is one of the leading causes of cancer-related fatalities in both the US and Europe. For the machines to learn how to locate the dangerous bacteria, researchers examined more than 25,000 pictures of blood samples. With the use of AI, the robots were able to learn to recognise these bacteria in the blood and predict their existence in fresh samples with a 95% accuracy rate, significantly lowering the fatality rate. They range from basic laboratory robots to extremely sophisticated surgical robots that can work alongside a human surgeon or carry out procedures on their own. They are used in hospitals and labs for repetitive jobs, rehabilitation, physical therapy, and support for people with long-term problems in addition to surgery. You can foun additiona information about ai customer service and artificial intelligence and NLP. The authors are grateful to the Editor-in-Chief for the suggestions and all the reviewers who spend a part of their time ensuring constructive feedback to our research article.

In addition, the discussion expands with Lu [93], which indicates that the excessive use of technology could hinder doctors’ skills and clinical procedures’ expansion. Among the main issues arising from the literature is the possible de-skilling of healthcare staff due to reduced autonomy in decision-making concerning patients [94]. 11 are expanded by also considering the ethical implications of technology and the role of skills. To do so, one needs precise disease definitions and a probabilistic analysis of symptoms and molecular profiles.

Another published study found that AI recognized skin cancer better than experienced doctors. US, German and French researchers used deep learning on more than 100,000 images to identify skin cancer. Comparing the results of AI to those of 58 international dermatologists, they found AI did better. Topol, an author of three books and over 1,200 peer-reviewed publications, is a prominent figure in digital medicine. The triage function is an algorithm tied to wearable devices that will use insights driven by health informatics to deliver real-time alerts to patients. In the event that a device detects an abnormal medical event, it will not only alert the wearer that there is a problem, it can even make the initial call to a physician or hospital.

The rapid progression of AI technology presents an opportunity for its application in clinical practice, potentially revolutionizing healthcare services. It is imperative to document and disseminate information regarding AI’s role in clinical practice, to equip healthcare providers with the knowledge and tools necessary for effective implementation in patient care. This review article aims to explore the current state of AI in healthcare, its potential benefits, limitations, and challenges, and to provide insights into its future development. By doing so, this review aims to contribute to a better understanding of AI’s role in healthcare and facilitate its integration into clinical practice. Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice.

Pfizer uses AI to aid its research into new drug candidates for treating various diseases. For example, the company used AI and machine learning to support the development of a Covid-19 treatment called PAXLOVID. Scientists at Pfizer are able to rely on modeling and simulation to identify compounds that have the highest likelihood of being effective treatment candidates so they can narrow their efforts. Global consulting firm ZS specializes in providing strategic support to businesses across various sectors, with a particular focus on healthcare, leveraging its expertise in AI, sales, marketing, analytics and digital transformation. ZS helps clients navigate complex challenges within industries such as medical technology, life sciences, health plans and pharmaceuticals, using advanced AI and analytics tools. AI can be used to support digital communications, offering schedule reminders, tailored health tips and suggested next steps to patients.

The results of collaboration between countries also present future researchers with the challenge of greater exchanges between researchers and professionals. Therefore, further research could investigate the difference in vision between professionals and academics. Third, the authors analysing the research findings and the issues under discussion strongly support AI’s role in decision support.

Although many AI tools are developed in academic research centers, partnering with private-sector companies is often the only way to commercialize the research. At times, these partnerships have resulted in the poor protection of privacy and cases in which patients were not always given control over the use of their information or were not fully informed about the privacy impacts. Technologies enabled by AI analytics allow patients to be evaluated in their home environments instead of taking valuable space in a hospital for monitoring situations, to improve outcomes and quality of life. In 1956, John McCarthy organized the Dartmouth Conference, where he coined the term “Artificial Intelligence.“ This event marked the beginning of the modern AI era.

importance of ai in healthcare

The ability of AI to aid in health diagnoses also improves the speed and accuracy of patient visits, leading to faster and more personalized care. And efficiently providing a seamless patient experience allows hospitals, clinics and physicians to treat more patients on a daily basis. Systems using cognitive computing, augmented reality, and body and voice movements are combined to generate this.

A study was conducted to validate this system as an open-label, prospective trial in patients with advanced solid tumors treated with three different chemotherapy regimens. CURATE.AI generated personalized doses for subsequent cycles based on the correlation between chemotherapy dose variation and tumor marker readouts. The integration of CURATE.AI into the clinical workflow showed successful incorporation and potential benefits in terms of reducing chemotherapy dose and improving patient response rates and durations compared to the standard of care. These findings support the need for prospective validation through randomized clinical trials and indicate the potential of AI in optimizing chemotherapy dosing and lowering the risk of adverse drug events.

These pioneering projects showcased AI’s potential to revolutionize diagnostics and personalized medicine. Ultimately, artificial intelligence in healthcare offers a refined way for healthcare providers to deliver better and faster patient care. By automating mundane administrative tasks, artificial intelligence can help medical professionals save time and money while also giving them more autonomy over their workflow process. Artificial intelligence in healthcare that uses deep learning is also used for speech recognition in the form of natural language processing. Features in deep learning models typically have little meaning to human observers and therefore the model’s results may be challenging to delineate without proper interpretation. As deep learning technology continues to advance, it will become increasingly important for healthcare professionals to understand how deep learning technology works and how to effectively use it in clinical settings.