Ari Nahum, MD, comments on the Original Article “Machine Learning–Based Patient Preference Prediction: A Proof of Concept.” Read the letter: nejm.ai/4qNgrzV #AI #MedSky #MLSky

Drawing on clinical scenarios demonstrating divergent value-based decisions, the authors of a new Perspective propose a framework using a transparent labeling system that documents how AI systems navigate value-laden clinical trade-offs. Learn more: nejm.ai/3ZvTtBe #AI #MedSky #MLSky

A new study demonstrates the successful integration of a real-time delayed cerebral ischemia prediction algorithm into a live intensive care unit environment using a silent validation methodology. Learn more: nejm.ai/4r8KL7R #AI #MedSky #MLSky

An editorial by Dr. Rebecca Sternschein explores the utility of multiple-choice questions and short-answer questions for assessment in medical education and whether a large language model can adequately grade short-answer questions. Read the editorial: nejm.ai/49GROh1 #AI #MedSky #MLSky

Models advanced. Biology lagged. On NEJM AI Grand Rounds, Dr. Marinka Zitnik explains why collaboration matters as much as computation. Listen to the full episode: nejm.ai/ep38 #AI #MedSky #MLSky

In a letter, Teva D. Brender, MD, and Alexander K. Smith, MD, comment on the Original Article “Machine Learning–Based Patient Preference Prediction: A Proof of Concept.” nejm.ai/3NC4IFN @alexsmithmd.bsky.social #AI #MedSky #MLSky

Parsa et al. propose the use of health AI target product profiles, which specify the performance thresholds an AI tool must meet to produce benefit within a specific care setting, accounting for workflow, capacity, and utility trade-offs. Learn more: nejm.ai/4qBoHTn #AI #MedSky #MLSky

A new study found that while grading short-answer responses from first-year medical students, GPT-4o achieved moderate agreement with human graders, suggesting that AI-assisted grading could help assess open-ended questions in medical education. Learn more: nejm.ai/4jJFYY9 #AI #MedSky #MLSky

Rare diseases are small in numbers — but huge in impact. On NEJM AI Grand Rounds, Dr. Marinka Zitnik explains why #AI trained across thousands of diseases could help change what’s possible. Hear more from Dr. Zitnik: nejm.ai/ep38 #MedSky #MLSky

A new Perspective by Venkatesh L. Murthy, MD, PhD, and Chirag J. Patel, PhD, explores what constitutes a high-value application in medical artificial intelligence. Read the full Perspective: nejm.ai/4jIBLUD @venkmurthy.bsky.social #AI #MedSky #MLSky

Editorial by Chirag J. Patel, PhD: Planning for an AlphaFold for Drug Safety Assessment: Benchmarking and Data Infrastructure as Prerequisites nejm.ai/44SwDHo #AI #MedSky #MLSky

A new study introduces TARGET-AI, a multimodal framework that integrates longitudinal EHR embeddings with contrastively pretrained ECG image representations to estimate pretest disease probability and guide targeted screening for structural heart disease. nejm.ai/4pU5qeI

Datasets, Benchmarks, and Protocols by P. Chung et al.: Verifying Facts in Patient Care Documents Generated by Large Language Models Using Electronic Health Records nejm.ai/4sm0Sk1 #AI #MedSky #MLSky

Policy Corner by R. Scheufen Tieghi et al.: The Promise of Animal Testing Alternatives at the U.S. Food and Drug Administration and National Institutes of Health nejm.ai/4svkOB6 #AI #MedSky #MLSky

Case Study by D. van de Sande et al.: Operationalization of Artificial Intelligence to Assist in Surgical Discharge: A Feasibility Case Study nejm.ai/3YJ1MJT #AI #MedSky #MLSky

Editorial by David Blumenthal, MD, MPP: Evolving Regulatory Science nejm.ai/4biPa3o @davidblumenthal.bsky.social #AI #MedSky #MLSky

Twelve to 13 years. Several billion dollars. On NEJM AI Grand Rounds, Dr. Marinka Zitnik breaks down the real cost of traditional drug development — and why alternatives matter. Listen to the full episode: nejm.ai/ep38 #AI #MedSky #MLSky

Volume 3, No. 2 of NEJM AI is now available! Here is a preview of the latest content: 𝗘𝗱𝗶𝘁𝗼𝗿𝗶𝗮𝗹 Grading LLMs on the Ability to Grade nejm.ai/49GROh1 𝗣𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲𝘀 Designing Clinically Useful AI: A Blueprint for Impact nejm.ai/4qBoHTn #MedSky #AI #MLSky

In a new editorial, Chirag J. Patel, PhD, argues that the operationalization of new approach methodologies to replace animal testing is currently hindered by a lack of benchmarking infrastructure. Read the full editorial: nejm.ai/44SwDHo #AI #MedSky #MLSky

Perspective by Nicholas Peoples, MD, MSc, MS, and Jennifer Blumenthal-Barby, PhD, MA: Dual Public Health and Regulatory Dilemmas of “Relational” Artificial Intelligence nejm.ai/3YqXczH #AI #MedSky #MLSky

A new study shows how VeriFact, a system designed to verify the accuracy of AI-generated clinical documents using data from patients’ EHRs, could be a scalable approach to ensuring reliability and trustworthiness in automated medical documentation. nejm.ai/4sm0Sk1 #AI #MedSky #MLSky

Perspective by Eike Petersen, PhD, and Frank Ursin, PhD (@frank_ursin): Against Disease Classification: Toward Continuous Disease Assessment in Precision Medicine nejm.ai/4aL3npB @epet.bsky.social @frankursin.bsky.social #AI #MedSky

A Policy Corner reviews the shift toward alternatives to animal testing in drug development and outlines initiatives to implement new approach methodologies to create a more ethical and human-relevant framework for preclinical safety and efficacy testing. nejm.ai/4svkOB6 #AI #MedSky #MLSky

In the latest episode of the AI Grand Rounds podcast, Dr. Marinka Zitnik of Harvard Medical School describes how AI-driven drug repurposing offers a way to work within existing constraints while still opening new therapeutic possibilities. Full episode: nejm.ai/ep38 #MedSky

Editorial by NEJM AI Editor-in-Chief Isaac Kohane, MD, PhD: The H-Index of Suspicion: How Culture, Incentives, and AI Challenge Scientific Integrity nejm.ai/4bipl3q #AI #MedSky #MLSky

In a new editorial, David Blumenthal, MD, MPP, writes that the FDA’s new approach to evaluating pharmaceuticals could be helpful to clinicians and patients, as long as it lives up to the highest standards of scientific inquiry. Read the full editorial: nejm.ai/4biPa3o @davidblumenthal.bsky.social

Perspective by Andrew S. Lea, MD, DPhil: Cognitive Aids, Artificial Intelligence, and Deskilling in Medicine: The History of an Enduring Anxiety nejm.ai/49gfudj @andrewlea.bsky.social #AI #MedSky #MLSky

A new study demonstrates that although the first prospective bedside deployment of the DESIRE #AI model achieved strong predictive performance and operational feasibility, its reliability was constrained by data quality and governance challenges. nejm.ai/3YJ1MJT #MedSky #MLSky

Case Study by M. Storey et al.: Early Clinical Evaluation of AI Triage of Chest Radiographs: Time to Diagnosis for Suspected Cancer and Number of Urgent CT Referrals nejm.ai/3Ngic9T #AI #MedSky #MLSky

The authors of a new Perspective warn that emotionally dependent attachments to #AI companions may potentially carry significant risks and argue for proactive clinical, research, and policy responses to anticipate harm and maximize societal benefits. nejm.ai/3YqXczH #MedSky #MLSky

Original Article by E. Chen et al.: International Retrospective Observational Study of Continual Learning for AI on Endotracheal Tube Placement from Chest Radiographs nejm.ai/3KZwdbt #AI #MedSky #MLSky

A new Perspective challenges the widespread use of disease classification in medical #AI, arguing that reducing continuous disease complexity to discrete classes fundamentally misrepresents pathophysiology and limits precision medicine. nejm.ai/4aL3npB @epet.bsky.social @frankursin.bsky.social

An editorial on generative #AI for scientific fakery highlights a growing problem: technical fixes may offer reassurance, but they can’t solve the deeper cultural pressures in science that reward speed and novelty over care and verification. Learn more: nejm.ai/4bipl3q #MedSky #MLSky

A new Perspective situates contemporary concerns about AI-driven cognitive offloading within a long history of debates over how reference tools — from early medical handbooks to digital systems — reshape viewpoints on clinical expertise. Learn more: nejm.ai/49gfudj @andrewlea.bsky.social

A letter highlights the need for #AI systems that restore physician presence and align technology with human values and argues that doctors who code must focus on the 60% of clinical work lost to inefficiency and administrative burden. Full letter: nejm.ai/4sr5QMk #MedSky #MLSky

An #AI triage system for detecting features of lung cancer on chest x-rays across a multihospital trust in London reduced the median time from chest x-ray to CT report without increasing overall CT volume. Full study results: nejm.ai/3Ngic9T #MedSky #MLSky

Using data from hospitals in 12 countries, a new study found that #AI models trained on continual learning for assessing endotracheal tube placement on chest radiographs consistently outperformed baseline and single-hospital fine-tuned models. Learn more: nejm.ai/3KZwdbt #MedSky #MLSky

Missed findings may matter more than incidental ones. On NEJM AI Grand Rounds, Dr. Zak Kohane explains why clinicians may soon run every scan through #AI as a second set of eyes. Listen to the full episode: nejm.ai/ep37 #MedSky #MLSky

Volume 3, No. 1 of NEJM AI is now available! Here is a preview of the latest content: 𝗘𝗱𝗶𝘁𝗼𝗿𝗶𝗮𝗹𝘀 Evolving Regulatory Science nejm.ai/4biPa3o #MedSky #AI #MLSky

Original Article by A. Bishara et al.: AI-Guided Surgical Blood Readiness: Overcoming Real-World Challenges in Prospective Validation for Safer, More Efficient Blood Preparation nejm.ai/3KAaTc9 #AI #MedSky #MLSky

Original Article by J.B. Moody et al.: A Foundation Transformer Model with Self-Supervised Learning for ECG-Based Assessment of Cardiac and Coronary Function nejm.ai/3XvciUi #AI #MedSky #MLSky

Policy Corner by N. Razavian et al.: Catalyzing Health AI by Fixing Payment Systems nejm.ai/44DVaiY #AI #MedSky #MLSky

Vibe coding works, but only if you know the system. On NEJM AI Grand Rounds, Dr. Zak Kohane breaks down why domain expertise still shapes AI’s usefulness. Listen to the full episode: nejm.ai/ep37 #AI #MedSky #MLSky

Perspective by A. Poddar et al.: Mitigating Limited Data Challenges to Improve Artificial Intelligence Integration in Rare Disease Drug Development nejm.ai/4peikVF #AI #MedSky #MLSky

Review Article by Soojin Park, MD, Yanwei Li, MS, and Murad Megjhani, PhD: Physiological Signals Boosted by Artificial Intelligence Save Time and Brain Function nejm.ai/4pu5OBD #AI #MedSky #NeuroSky

#AI turned hours into minutes. Dr. Zak Kohane describes how he built his own EHR — showing clinicians what true augmentation looks like on NEJM AI Grand Rounds. Hear more from Dr. Kohane: nejm.ai/ep37 #MedSky #MLSky

A new article presents the development and silent prospective validation of Smart Match, a machine-learning system designed to predict patient-specific perioperative blood transfusion needs. Learn more about this system: nejm.ai/3KAaTc9 #AI #MedSky #MLSky

A new study introduces a self-supervised electrocardiogram transformer foundation model that achieves high diagnostic accuracy across multiple cardiac prediction tasks, expanding AI’s potential in complex diagnostic areas. Learn more: nejm.ai/3XvciUi #AI #MedSky #MLSky

Original Article by P.J. Lukac et al.: Ambient AI Scribes in Clinical Practice: A Randomized Trial nejm.ai/3MwD0cJ  #AI #MedSky #MLSky

Perspective by Bilal Irfan, MS, J. Wesley Boyd, MD, PhD, and Roberto Daniel Sirvent, JD, PhD: When Protecting Privacy Means Protecting Health: Foreseeable Health Harms of AI Language Translation and Interpretation Technologies for Immigrant Patients nejm.ai/49PrjYr #AI #MedSky #MLSky