From the Joint Commission and CHAI: A Clinical Roadmap for Responsible AI Integration
Artificial intelligence (AI) is no longer a distant innovation; it’s rapidly reshaping the clinical environment. From diagnostic imaging and risk stratification to staffing optimization and patient engagement, AI has become an integral part of modern healthcare delivery. Yet, as the Joint Commission and the Coalition for Health AI (CHAI) emphasize in their Guidance on the […]
Streamlining Clinical Research with AI: A Guide for Resident Physicians and Clinicians
AIMEDICINEUPDATE.COM 8/4/2025 For resident physicians and early-career clinicians, conducting research often feels like an uphill battle. Time is limited, administrative burdens are high, and academic mentorship may not always be easily accessible. Yet the desire to contribute to the scientific community and improve patient care remains strong. Fortunately, artificial intelligence (AI)—especially general-purpose tools like ChatGPT […]
Avoiding Hallucinations in Large-Language-Model Output: A 2025 Field Guide
aimedicineupdate.com July 20, 2025 Even after two years of rapid model upgrades, generative systems can still invent dates, mis-attribute quotations, or cite sources that do not exist. Microsoft researchers call these slip-ups ungrounded content, answers that look fluent but cannot be traced to any reliable evidence (source). The very word “hallucination” in AI, although contested […]
Rethinking the EHR Experience: Stanford’s ChatEHR Pilot and What Clinicians Are Saying
June 8, 2025 Stanford Medicine’s recent announcement of ChatEHR—a new large language model (LLM) interface embedded directly into the Epic electronic health record (EHR)—has drawn substantial attention from across the medical and health tech community. The initiative, currently in pilot phase, aims to relieve clinicians from one of the most pressing burdens of modern care: […]
Bridging the Gap: Accelerating Scientific Publishing in the Age of Rapid AI Advancement
The Speed of Innovation Surpasses Peer Review Over the past decade, AI research has evolved from a niche scientific endeavor to a global enterprise driving advancements across disciplines. As of 2019, artificial intelligence preprints were submitted to the open-access repository arXiv at a rate exceeding three per hour, a 148-fold increase compared to 1994, […]
When Chatbots Beat the Virologists: What the New “VCT” Benchmark Really Means
Ever wondered how far large-language models have crept into hands-on lab science? A new test called the Virology Capabilities Test (VCT) just set the bar—and the results are eye-opening. The Quick Story Researchers at SecureBio and the Center for AI Safety rounded up dozens of PhD-level virologists to build 322 complex questions—many with electron microcopy […]
Two AI Paradigms in Medical Education: The Generative Tutor and the Agentic Coach
Introduction: Medical training is at a pivotal moment, with generative AI already reshaping educational practices as reliable, on-demand tutors that deliver instant knowledge and feedback, while agentic AI is poised to further revolutionize medical training as proactive, autonomous coaches guiding learners through dynamic clinical scenarios. Together, these AI paradigms offer complementary benefits in educating future […]
AI Prompting for Clinicians
In the rapidly evolving landscape of healthcare, artificial intelligence (AI) has become an invaluable tool for physicians, medical students, and residents. From diagnostic assistance to personalized treatment plans, AI’s applications are vast and transformative.
The Need for AI Literacy in Medical Education
The rapid integration of artificial intelligence (AI) into medicine is reshaping clinical practice, research, and medical education. Large language models (LLMs) such as ChatGPT, Claude, and Bard have demonstrated capabilities in passing medical licensing exams, assisting with clinical decision-making, and enhancing medical training. However, despite the widespread adoption of AI tools among medical students, most receive little or no formal training on their responsible and effective use.
Large Language Models Limitations
Artificial Intelligence (AI) Large Language Models (LLMs) are reshaping the medical landscape, offering new ways to support clinicians, students, and researchers. While these models can enhance efficiency and knowledge-sharing, it is essential to recognize both their strengths and limitations.