NEJM AI

Volume 2, No. 8 of NEJM AI is now available! Here are the latest articles:   Editorial: AI-Driven OSCE Preparation in Medical Education: Promise, Pitfalls, and Practical Implications nejm.ai/3GyaXat 🔖 Save for later and share with a friend

Original Article by T. Adnan et al.: AI-Enabled Parkinson’s Disease Screening Using Smile Videos nejm.ai/4nk6PeD #ArtificialIntelligence #Neurology

In a new Perspective, R. Andrew Taylor, MD, MHS, frames AI agents as a transformative advancement in health care AI, offering unprecedented capabilities but raising complex ethical challenges. Learn more: nejm.ai/4lDyK81

ECGFounder, a general-purpose foundation model for cardiovascular disease detection, demonstrates strong generalization and outperforms baseline models on diverse tasks, enabling scalable, cloud-integrated cardiac monitoring. Learn more: nejm.ai/3TJHs8q

Six frontier large language models evaluated on incorporating newly updated medical knowledge through commercial fine-tuning application programming interfaces struggled to generalize updated information, despite modest gains. Learn more: nejm.ai/4nTx1Np

In an editorial, V. L. Murthy, MD, PhD, writes that we may be entering an era of specialist–generalist medical AI paradox, wherein AI more rapidly advances in performing tasks that humans require specialization to perform than in general medical tasks. nejm.ai/4nm6054

The authors of a new editorial examine the use of generative AI to simulate patient encounters for students preparing for the Objective Structured Clinical Examination, highlighting both its pedagogical promise and potential risks. Learn more: nejm.ai/3GyaXat

SpikeNet2, a deep-learning model shown to achieve expert-level performance in detecting epileptiform discharges from EEG recordings while significantly reducing false positives, demonstrates strong generalizability across diverse datasets. Learn more: nejm.ai/4lq1Qr4

Lavigne and colleagues evaluate the AI-Standardized Clinical Examination framework, which leverages text-based simulations with virtual patients and AI-driven assessment. Read the full study results: nejm.ai/3TEiuHO

An AI-based screening tool for Parkinson’s disease (PD) that analyzes facial expressions demonstrated strong accuracy in identifying PD across diverse populations and settings, highlighting its potential for scalable, remote PD screening. Learn more: nejm.ai/4nk6PeD

Perspective by Y. Qiu et al.: The Landscape of Medical AI in China nejm.ai/40kSswH #ArtificialIntelligence #GlobalHealth

For some first-year medical students, training alongside an ambient AI scribe during standardized patient interviews ultimately led to professional growth and a deeper understanding of how human skills can complement AI in clinical practice. Learn more: nejm.ai/44VgDU8

Poignant and insightful view by medical students on the impact of AI and the role of humans in clinical care @NEJM_AI ai.nejm.org/doi/10.1056/AI… We need to figure out how to make students like these our future leaders in healthcare.

A new Perspective explores the emerging role of causal machine learning in precision oncology, highlighting its potential to improve individualized treatment decisions by estimating patient-specific treatment effects. Learn more: nejm.ai/3GOpfnl