Journal of Medical Internet Research

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Future Use of AI in Diagnostic Medicine: 2-Wave Cross-Sectional Survey Study

All these factors mean that the future of AI use in diagnostic medicine is still quite uncertain, despite its potential. What, then, is the future of AI use in diagnostic medicine? This study aimed to anticipate future possibilities of AI use in diagnostic medicine, comparing researchers’ expectations over time.

Bernardo Pereira Cabral, Luiza Amara Maciel Braga, Carlos Gilbert Conte Filho, Bruno Penteado, Sandro Luis Freire de Castro Silva, Leonardo Castro, Marcelo Fornazin, Fabio Mota

J Med Internet Res 2025;27:e53892

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Potential of Large Language Models in Health Care: Delphi Study

Such work can guide future research and development efforts to effectively address specific health care challenges. Overall, the objectives of our study were to seek researchers’ opinions on (1) the likelihood that LLMs will be adopted in health care and for what purposes, (2) the likely benefits of LLMs in health care, (3) the shortcomings and risks of LLM adoption in health care, (4) the requirements for the adoption of LLMs in health care, and (5) the reliability of LLMs in future health care.

Kerstin Denecke, Richard May, LLMHealthGroup, Octavio Rivera Romero

J Med Internet Res 2024;26:e52399

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AI-Enabled Medical Education: Threads of Change, Promising Futures, and Risky Realities Across Four Potential Future Worlds

As AI continues to transform various aspects of our lives, one critical question arises for medical education: what will be the nature of education, teaching, and learning in a future world where the acquisition, retention, and application of knowledge in the traditional sense are fundamentally altered by AI? This paper will explore the future of medical education spanning all levels of training, in 4 theoretical worlds increasingly driven by AI.

Michelle I Knopp, Eric J Warm, Danielle Weber, Matthew Kelleher, Benjamin Kinnear, Daniel J Schumacher, Sally A Santen, Eneida Mendonça, Laurah Turner

JMIR Med Educ 2023;9:e50373

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The Impact of Multimodal Large Language Models on Health Care’s Future

As medicine is a multimodal discipline, the potential future versions of LLMs that can handle multimodality—meaning that they could interpret and generate not only text but also images, videos, sound, and even comprehensive documents—can be conceptualized as a significant evolution in the field of AI. Such advancements would enable more holistic patient assessments, drawing from diverse data sources for accurate diagnoses and treatment recommendations.

Bertalan Meskó

J Med Internet Res 2023;25:e52865

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Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial

While the technical details and background of generative AI will probably be included in future curricula, it would be useful for medical students to learn the most practical tips of using LLMs even before that happens. The general message for every LLM user should be that they could use such AI tools to expand their knowledge, capabilities, and ideas instead of solving things on their behalf.

Bertalan Meskó

J Med Internet Res 2023;25:e50638

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The ChatGPT (Generative Artificial Intelligence) Revolution Has Made Artificial Intelligence Approachable for Medical Professionals

Medical curricula, guidelines of medical associations, and the general discussion about AI’s future role in our profession must adjust accordingly. Medical curricula could involve teaching prompt engineering to provide knowledge, skills, and a mindset for medical professionals to become proficient users of generative AI.

Bertalan Mesko

J Med Internet Res 2023;25:e48392

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Forecasting Artificial Intelligence Trends in Health Care: Systematic International Patent Analysis

A better understanding of which medical specialties will be impacted by AI in the near future might shed light on what guidelines, policies, or frameworks to dedicate enough efforts to next. Also, while the number of peer-reviewed papers on AI’s role in health care and medicine, relevant patents, and commercially available AI and ML devices keeps on growing at an unprecedented rate, it will become increasingly difficult for regulators and policy makers to keep up with the pace of innovation [4].

Stan Benjamens, Pranavsingh Dhunnoo, Márton Görög, Bertalan Mesko

JMIR AI 2023;2:e47283

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