Clinician voices on ethics of LLM integration in healthcare: a thematic analysis of ethical concerns and implications DOI Creative Commons
Tala Mirzaei, Leila Amini, Pouyan Esmaeilzadeh

и другие.

BMC Medical Informatics and Decision Making, Год журнала: 2024, Номер 24(1)

Опубликована: Сен. 9, 2024

Язык: Английский

Generative artificial intelligence in healthcare: A scoping review on benefits, challenges and applications DOI
Khadijeh Moulaei,

Atiye Yadegari,

Mahdi Baharestani

и другие.

International Journal of Medical Informatics, Год журнала: 2024, Номер 188, С. 105474 - 105474

Опубликована: Май 8, 2024

Язык: Английский

Процитировано

41

Higher Education’s Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania DOI Open Access

Juergen Rudolph,

Fadhil Mohamed Mohamed Ismail,

Ştefan Popenici

и другие.

Journal of University Teaching and Learning Practice, Год журнала: 2024, Номер 21(06)

Опубликована: Апрель 19, 2024

Higher education is currently under a significant transformation due to the emergence of generative artificial intelligence (GenAI) technologies, hype surrounding GenAI and increasing influence educational technology business groups over tertiary education. This commentary, prepared for Special Issue Journal University Teaching & Learning Practice (JUTLP) on “Enhancing student engagement using Artificial Intelligence (AI) chatbots,” delves into complex landscape opportunities threats that AI chatbots, including ChatGPT, introduce realm higher We argue while offers promise in enhancing pedagogy, research, administration, support, concerns around academic integrity, labour displacement, embedded biases, environmental sustainability, increased commercialisation, regulatory gaps necessitate critical approach. Our commentary advocates development literacy among educators students, emphasising necessity foster an environment responsible innovation informed use AI. posit successful integration must be grounded principles ethics, equity, prioritisation aims human values. By offering nuanced exploration these issues, our contribute ongoing discourse how institutions can navigate rise GenAI, ensuring technological advancements benefit all stakeholders upholding core

Язык: Английский

Процитировано

33

The Role of Large Language Models in Transforming Emergency Medicine: Scoping Review DOI Creative Commons
Carl Preiksaitis, Nicholas Ashenburg,

Gabrielle Bunney

и другие.

JMIR Medical Informatics, Год журнала: 2024, Номер 12, С. e53787 - e53787

Опубликована: Апрель 5, 2024

Background Artificial intelligence (AI), more specifically large language models (LLMs), holds significant potential in revolutionizing emergency care delivery by optimizing clinical workflows and enhancing the quality of decision-making. Although enthusiasm for integrating LLMs into medicine (EM) is growing, existing literature characterized a disparate collection individual studies, conceptual analyses, preliminary implementations. Given these complexities gaps understanding, cohesive framework needed to comprehend body knowledge on application EM. Objective absence comprehensive exploring roles EM, this scoping review aims systematically map LLMs’ applications within EM identify directions future research. Addressing gap will allow informed advancements field. Methods Using PRISMA-ScR (Preferred Reporting Items Systematic Reviews Meta-Analyses extension Scoping Reviews) criteria, we searched Ovid MEDLINE, Embase, Web Science, Google Scholar papers published between January 2018 August 2023 that discussed use We excluded other forms AI. A total 1994 unique titles abstracts were screened, each full-text paper was independently reviewed 2 authors. Data abstracted independently, 5 authors performed collaborative quantitative qualitative synthesis data. Results 43 included. Studies predominantly from 2022 conducted United States China. uncovered four major themes: (1) decision-making support highlighted as pivotal area, with playing substantial role patient care, notably through their real-time triage, allowing early recognition urgency; (2) efficiency, workflow, information management demonstrated capacity significantly boost operational particularly automation record synthesis, which could reduce administrative burden enhance patient-centric care; (3) risks, ethics, transparency identified areas concern, especially regarding reliability outputs, specific studies challenges ensuring unbiased amidst potentially flawed training data sets, stressing importance thorough validation ethical oversight; (4) education communication possibilities included enrich medical training, such using simulated interactions skills. Conclusions have fundamentally transform decision-making, workflows, improving outcomes. This sets stage identifying key research areas: prospective LLM applications, establishing standards responsible use, understanding provider perceptions, physicians’ AI literacy. Effective integration require efforts evaluation ensure technologies can be safely effectively applied.

Язык: Английский

Процитировано

31

Twelve tips on creating and using custom GPTs to enhance health professions education DOI
Ken Masters, Jennifer Benjamin, Anoop Agrawal

и другие.

Medical Teacher, Год журнала: 2024, Номер 46(6), С. 752 - 756

Опубликована: Янв. 29, 2024

The custom GPT is the latest powerful feature added to ChatGPT. Non-programmers can create and share their own GPTs ("chat bots"), allowing Health Professions Educators apply capabilities of ChatGPT administrative assistants, online tutors, virtual patients, more, support clinical non-clinical teaching environments. To achieve this correctly, however, requires some skills, 12-Tips paper provides those: we explain how construct data sources, build relevant GPTs, basic security.

Язык: Английский

Процитировано

25

Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review DOI Creative Commons
Xiaojun Xu, Y.J. Chen, Jing Miao

и другие.

Journal of Educational Evaluation for Health Professions, Год журнала: 2024, Номер 21, С. 6 - 6

Опубликована: Март 15, 2024

ChatGPT is a large language model (LLM) based on artificial intelligence (AI) capable of responding in multiple languages and generating nuanced highly complex responses. While holds promising applications medical education, its limitations potential risks cannot be ignored.

Язык: Английский

Процитировано

24

Reference Hallucination Score for Medical Artificial Intelligence Chatbots: Development and Usability Study DOI Creative Commons
Fadi Aljamaan, Mohamad‐Hani Temsah, Ibraheem Altamimi

и другие.

JMIR Medical Informatics, Год журнала: 2024, Номер 12, С. e54345 - e54345

Опубликована: Июль 3, 2024

Artificial intelligence (AI) chatbots have recently gained use in medical practice by health care practitioners. Interestingly, the output of these AI was found to varying degrees hallucination content and references. Such hallucinations generate doubts about their implementation.

Язык: Английский

Процитировано

22

Art or Artifact: Evaluating the Accuracy, Appeal, and Educational Value of AI-Generated Imagery in DALL·E 3 for Illustrating Congenital Heart Diseases DOI
Mohamad‐Hani Temsah, Abdullah Alhuzaimi, Mohammed Almansour

и другие.

Journal of Medical Systems, Год журнала: 2024, Номер 48(1)

Опубликована: Май 23, 2024

Язык: Английский

Процитировано

19

Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome DOI Creative Commons
Ajay Kumar, Pierce Burr, Timothy Young

и другие.

JMIR Medical Education, Год журнала: 2024, Номер 10, С. e52155 - e52155

Опубликована: Янв. 29, 2024

Our research letter investigates the potential, as well current limitations, of widely available text-to-image tools in generating images for medical education. We focused on illustrations important physical signs face (for which confidentiality issues conventional patient photograph use may be a particular concern) that medics should know about, and we used facial hypothyroidism Horner syndrome examples.

Язык: Английский

Процитировано

15

Diagnosis of malignancy in oropharyngeal confocal laser endomicroscopy using GPT 4.0 with vision DOI
Matti Sievert, Marc Aubreville, Sarina K. Mueller

и другие.

European Archives of Oto-Rhino-Laryngology, Год журнала: 2024, Номер 281(4), С. 2115 - 2122

Опубликована: Фев. 8, 2024

Язык: Английский

Процитировано

15

A systematic review of the impact of artificial intelligence on educational outcomes in health professions education DOI Creative Commons
Eva Feigerlová,

Hind Hani,

Ellie Hothersall-Davies

и другие.

BMC Medical Education, Год журнала: 2025, Номер 25(1)

Опубликована: Янв. 27, 2025

Язык: Английский

Процитировано

4