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NEJM AI
@ai.nejm.org
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NEJM AI, a new monthly journal from the publisher of @nejm.org, explores the cutting-edge applications of artificial intelligence and machine learning in clinical medicine. Online at ai.nejm.org.
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NEJM AI @ai.nejm.org · 25d
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

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AI Grand Rounds Episode 38 Bridging AI and Biology to Tackle Medicine’s Hardest Problems with Dr. Marinka Zitnik Photo of Dr. Zitnik
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Perspective by Venkatesh L. Murthy, MD, PhD, and Chirag J. Patel, PhD: The Paradoxical Challenge of High-Value Medical Artificial Intelligence nejm.ai/4jIBLUD

@venkmurthy.bsky.social #AI #MedSky #MLSky
Figure 1. Central Paradox.
February 13, 2026 at 7:15 PM
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Original Article by E.K. Oikonomou et al.: TARGET-AI: A Foundational Approach for the Targeted Deployment of Artificial Intelligence Electrocardiography in the Electronic Health Record nejm.ai/4pU5qeI

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Figure 1. Targeted Deployment of AI Screening Technologies in the EHR.
February 13, 2026 at 2:30 PM
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In a new study evaluating seven chatbots for their ability to provide support for alcohol misuse through simulated 7-day interactions, clinician raters found that while the bots showed empathy, the quality and accuracy of the information varied widely. nejm.ai/4bi0wF2

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Table 2. Chatbot Characteristics. Table 3. Overall Performance and Individual Evaluation Criteria Scores.
February 12, 2026 at 6:30 PM
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From action to feedback to learning. On NEJM AI Grand Rounds, Dr. Marinka Zitnik explains why #AI agents matter for scientific discovery. Hear more from Dr. Zitnik: nejm.ai/ep38

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February 12, 2026 at 1:31 PM
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Ari Nahum, MD, comments on the Original Article “Machine Learning–Based Patient Preference Prediction: A Proof of Concept.” Read the letter: nejm.ai/4qNgrzV

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Page 1 of the letter "Model Performance Convergence Highlights Data Limitations in a Patient Preference Predictor" Read the full letter at ai.nejm.org.
February 11, 2026 at 5:15 PM
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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

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“Law, ethics, and practice guidelines traditionally address those differences by prioritizing patient autonomy, clinician beneficence, fairness, and treatment utility. Yet, the patient whose health is on the line and the clinician committed to caring for them have no way of knowing what values are actually embedded in the AI systems they use.” Perspective “The Missing Dimension in Clinical AI: Making Hidden Values Visible” by C. Goldberg et al.
February 11, 2026 at 1:30 PM
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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

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Figure 2. Overview of the ICU Cockpit Visual Interface.
February 10, 2026 at 6:15 PM
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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

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Editorial Kuling et al. take an important step in the exploration of how LLMs may enable wider use of [short answer questions], allowing a powerful formative assessment tool for clinically relevant reasoning skills to be a key aspect of the future of medical education. “Grading LLMs on the Ability to Grade” by Rebecca Sternschein, M.D., M.H.P.E.
February 10, 2026 at 2:30 PM
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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

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February 9, 2026 at 1:31 PM
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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

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Page 1 of the letter "Machine Learning Can Assist Surrogate Decision-Makers." Read the full letter at ai.nejm.org.
February 6, 2026 at 2:26 PM
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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

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“Meaningful evaluation of AI in health care must move beyond only diagnostic accuracy performance metrics and must adopt a proactive approach to identify the true needs in systems where AI can advance care.” Perspective “Designing Clinically Useful AI: A Blueprint for Impact” by S. Parsa et al.
February 5, 2026 at 2:30 PM
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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

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Figure 1. Study Flow Diagram for Human and GPT-4o Grading of Short-Answer Responses.
February 4, 2026 at 5:31 PM
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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

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February 4, 2026 at 2:16 PM
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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

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“Regardless of one’s feelings about the potential of medical AI, a shift from intellectually interesting problems with relatively niche clinical applications, which dominated the first phase of this field, to solving high-value medical problems ... is overdue.” Perspective “The Paradoxical Challenge of High-Value Medical Artificial Intelligence” by Venkatesh L. Murthy, M.D., Ph.D., and Chirag J. Patel, Ph.D.
February 3, 2026 at 6:30 PM
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Editorial by Chirag J. Patel, PhD: Planning for an AlphaFold for Drug Safety Assessment: Benchmarking and Data Infrastructure as Prerequisites nejm.ai/44SwDHo

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Page 1 of the editorial "Planning for an AlphaFold for Drug Safety Assessment: Benchmarking and Data Infrastructure as Prerequisites" Bottom: Read the full editorial at ai.nejm.org.
February 3, 2026 at 2:04 PM
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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
Futuristic digital illustration of a cube with a heart icon at its center, surrounded by floating medical records and EKG graphs. Original Article TARGET-AI: A Foundational Approach for the Targeted Deployment of Artificial Intelligence Electrocardiography in the Electronic Health Record E.K. Oikonomou and Others
February 2, 2026 at 6:15 PM
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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

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Figure 1. VeriFact Evaluation of a Large Language Model–Generated Clinical Narrative. Figure 2. VeriFact System Architecture. Figure 3. VeriFact Performance for Large Language Model–Generated Brief Hospital Course Narratives Evaluated Using Atomic Claim Propositions.
February 2, 2026 at 1:30 PM
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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

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Table 1. Example Validation Criteria for New Approach Methodologies.
January 30, 2026 at 2:26 PM
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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

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Figure 1. Distribution of Surgery Duration. Figure 2. Confusion Matrix for Postoperative Day Two Discharge Prediction. Figure 3. Model Performance on the 114 Patients.
January 29, 2026 at 2:15 PM
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Editorial by David Blumenthal, MD, MPP: Evolving Regulatory Science nejm.ai/4biPa3o

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Page 1 of the editorial "Evolving Regulatory Science" Bottom: Read the full editorial at ai.nejm.org.
January 28, 2026 at 2:17 PM
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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

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January 27, 2026 at 5:31 PM
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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
The cover of the February 2026 issue of NEJM AI with "NEW ISSUE NOW AVAILABLE" above it.
January 27, 2026 at 1:30 PM
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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

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“An all-in AI platform will require more than new assays or algorithms. The field must commit to creating the infrastructure and standards for the community, which include clear prediction tasks, open data, and recurring evaluations by all parties, including regulators.” Editorial “Planning for an AlphaFold for Drug Safety Assessment: Benchmarking and Data Infrastructure as Prerequisites” by Chirag J. Patel, Ph.D.
January 26, 2026 at 2:32 PM
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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

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Page 1 of the Perspective "Dual Public Health and Regulatory Dilemmas of 'Relational' Artificial Intelligence" Bottom: Read the full article at ai.nejm.org.
January 23, 2026 at 5:30 PM
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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

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Figure 1. Disease Classification AI versus Continuous Disease Assessment AI.
January 23, 2026 at 1:30 PM