Healthcare Generative Artificial Intelligence Tools in Medical Diagnosis, Treatment, and Prognosis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F23%3A00002640" target="_blank" >RIV/75081431:_____/23:00002640 - isvavai.cz</a>

Výsledek na webu

<a href="https://addletonacademicpublishers.com/contents-crlsj/2779-volume-15-1-2023/4504-healthcare-generative-artificial-intelligence-tools-in-medical-diagnosis-treatment-and-prognosis" target="_blank" >https://addletonacademicpublishers.com/contents-crlsj/2779-volume-15-1-2023/4504-healthcare-generative-artificial-intelligence-tools-in-medical-diagnosis-treatment-and-prognosis</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Healthcare Generative Artificial Intelligence Tools in Medical Diagnosis, Treatment, and Prognosis

Popis výsledku v původním jazyce

This paper provides a systematic literature review of studies inves-tigating how ChatGPT can be deployed in clinical decision support and practice, producing precise differential diagnosis lists and providing reliable disease and medical query-related information with regard to real-time monitoring and personalized treatment. The analysis highlights that generative artificial intelligence tools enable medical decision-making and analyze patient data, resulting in better patient outcomes and in enhanced access to care. Throughout March 2023, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “healthcare genera tive artificial intelligence tools” + “medical diagnosis,” “medical treatment,” and “medical prognosis.” As we inspected research published in 2023, only 174 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 38, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Název v anglickém jazyce

Healthcare Generative Artificial Intelligence Tools in Medical Diagnosis, Treatment, and Prognosis

Popis výsledku anglicky

This paper provides a systematic literature review of studies inves-tigating how ChatGPT can be deployed in clinical decision support and practice, producing precise differential diagnosis lists and providing reliable disease and medical query-related information with regard to real-time monitoring and personalized treatment. The analysis highlights that generative artificial intelligence tools enable medical decision-making and analyze patient data, resulting in better patient outcomes and in enhanced access to care. Throughout March 2023, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “healthcare genera tive artificial intelligence tools” + “medical diagnosis,” “medical treatment,” and “medical prognosis.” As we inspected research published in 2023, only 174 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 38, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, MMAT, and ROBIS.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

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OECD FORD obor

50200 - Economics and Business

Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Contemporary Readings in Law and Social Justice

ISSN

1948-9137

e-ISSN

2162-2752

Svazek periodika

15

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

81-98

Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-85168337999