AI in Medicine Update — AudioScholar

Editor's Pick: Overuse and False Restraint in Large Language Model Recommendations for Choosing Wisely Scenarios (Annals of Internal Medicine, 2026)

This AudioScholar briefing is generated by artificial intelligence for healthcare professionals and trainees. It is not medical advice.

Welcome to your weekly update in AI in Medicine. This period has three threads. Language models are being tested as diagnosticians, as advisers on low-value care, and as personal health coaches, and the results look strong on benchmarks but uneven where cost and restraint matter. Machine-learning aging clocks keep multiplying, and they now disagree about whether one clock can serve everyone.

This week's papers:

1. Sequential diagnosis with language models. — Science 2026
2. Overuse and False Restraint in Large Language Model Recommendations for Choosing Wisely Scenarios. — Annals of Internal Medicine 2026
3. The anatomy of a personal health agent. — Nature 2026
4. Rapid patient-specific neural networks for X-ray to volume registration. — Nature 2026
5. Artificial intelligence-enabled clinical phenotyping of human brown fat. — Nature 2026
6. Sex-specific biological aging clocks across organs and omics. — Nature Medicine 2026
7. A machine learning-derived aging index for risk stratification and mortality prediction in cardiovascular-kidney-metabolic syndrome: A retrospective cohort study. — PLOS Medicine 2026
8. Metabolomic aging and mortality clocks based on ensemble learning identify systemic aging risk across the human life span in 18,476 individuals. — Science Translational Medicine 2026
9. Trastuzumab plus nivolumab with gemcitabine and cisplatin as first-line therapy for HER2-positive unresectable biliary tract cancer: a phase 1b/2 trial. — Nature Medicine 2026

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Editor's Pick: Reporting completeness of clinical trials evaluating large language model interventions in medicine: systematic review (BMJ, 2026)

This AudioScholar briefing is generated by artificial intelligence for healthcare professionals and trainees. It is not medical advice.

Welcome to your weekly update in AI in Medicine. Three threads run through this period's papers. First, AI has quietly become part of everyday clinical reasoning, mostly for treatment decisions, and it is now entering the consultation itself. Second, the evidence base behind these tools is thinner and less reproducible than that adoption would suggest.

This week's papers:

1. Clinician Use of an Artificial Intelligence-Enabled Clinical Information Platform. — JAMA 2026
2. Reporting completeness of clinical trials evaluating large language model interventions in medicine: systematic review. — BMJ 2026
3. Human-artificial intelligence collaboration for comanaging epilepsy in real time. — Nature Medicine 2026
4. An open vision-language model for diverse medical applications. — Nature Medicine 2026
5. AI-assisted scoping review of code sharing in clinical prediction model research. — Nature Medicine 2026
6. Ambient scribes as narrative technologies. — The Lancet 2026
7. Histological aging signatures for monitoring tissue-specific aging and disease. — Nature Medicine 2026
8. Metabolic determinants of cancer immunotherapy outcomes identified by plasma profiling. — Nature Medicine 2026
9. Blood-based circular RNAs for early diagnosis of Alzheimer's disease. — Nature Medicine 2026

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Editor's Pick: Prospective evaluation of a large language model clinical decision support system in the emergency department (Nature Medicine, 2026)

This AudioScholar briefing is generated by artificial intelligence for healthcare professionals and trainees. It is not medical advice.

Welcome to your weekly update in AI in Medicine. This period, the evidence moves out of the benchmark and into the building. Prospective deployments of language models in an emergency department and a primary care clinic suggest that accuracy may no longer be the hard part, and that keeping clinicians engaged is.

This week's papers:

1. Prospective evaluation of a large language model clinical decision support system in the emergency department. — Nature Medicine 2026
2. Conversational diagnostic artificial intelligence in ambulatory primary care: a prospective feasibility study. — The Lancet 2026
3. Large-scale AI-guided liver malignancy diagnosis: multicenter study and a single-arm trial. — Nature Medicine 2026
4. Electrocardiogram-Based Deep Learning to Prioritize Testing for Transthyretin Amyloid Cardiomyopathy. — JAMA 2026
5. Large-scale esophageal cancer screening through noncontrast computed tomography and artificial intelligence. — Nature Medicine 2026
6. A clinically-oriented foundation model for intraoperative pathology. — Nature Medicine 2026
7. On-premise medical AI agents for reliable clinical decision-making. — Nature Medicine 2026
8. A clinically validated framework for auditing AI chatbot behavior in mental health interactions. — Nature Medicine 2026
9. Ethics and Professionalism in Artificial Intelligence and Medical Practice: A Position Paper From the American College of Physicians. — Annals of Internal Medicine 2026
10. Prediction of maternal and infant outcomes from longitudinal electronic health records with a mother-child AI agent. — Nature Medicine 2026

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This AudioScholar briefing is generated by artificial intelligence for healthcare professionals and trainees. It is not medical advice.

This week's papers:

1. Clinical decision support in hematological malignancies using a case-grounded AI agent. — Nature Medicine
2. Call to Action: Accelerating AI-driven Transformation in Medical Imaging and the Broader Health Care System. — Radiology
3. Generalizable AI predicts immunotherapy outcomes across cancers and treatments. — Nature Medicine
4. Evaluating the robustness and readiness of large frontier models in health AI applications. — Nature Medicine
5. How I Do It: Understanding and Leveraging Generative AI for Chest Radiology Reporting. — Radiology
6. End-to-end multimodal pathology foundation model with clinical dialogue. — Nature Medicine
7. Disparate privacy risks from medical AI. — Nature
8. A Strategic Framework to Address Growing Imbalances between Physician Supply and Demand for Radiology: A Review from the International Society for Strategic Studies in Radiology. — Radiology
9. In vivo feasibility study of humanoid robots in surgery. — Nature
10. The Virtual Tissues foundation model resolves spatial proteomics across scales. — Nature

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This AudioScholar briefing is generated by artificial intelligence for healthcare professionals and trainees. It is not medical advice.

This week's papers:

1. Clinical usability of an explainable AI decision support tool and evaluation of multimodal models in NSCLC. — Nature Medicine
2. Deep Learning-derived Bone Mineral Density and Longitudinal White Matter Microstructure and Cognitive Decline: Multi-Ethnic Study of Atherosclerosis. — Radiology
3. Opportunistic Chest CT Paraspinal Muscle Biomarkers to Predict Longitudinal Thoracic Vertebral Bone Mineral Density Loss: Results from MESA. — Radiology
4. Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease. — Science Translational Medicine
5. Multimodal protective and susceptibility clusters in paediatric atopic dermatitis: A machine learning-based, data-driven observational study. — PLOS Medicine

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Welcome to your weekly update in AI in Medicine.

This week's papers:

1. AI-based clinician decision support system for diagnosis of inherited retinal diseases: a multicenter, randomized trial. — Nature Medicine
2. Bridging the Generalist-Subspecialist Gap with GPT-5-Thinking: Dual-Center Evaluation in Orbital and Head-and-Neck Tumor MRI Reports. — Radiology
3. Improving Recognition Performance and Reader Efficiency for Femoral-Neck Fracture Detection on Pelvic or Hip Radiographs Using Artificial Intelligence. — Radiology
4. Multinational Validation of a Radiography-Based AI Tool for Appendicular Fracture Detection and Corresponding Reader Performance. — Radiology
5. Passive heart-rate monitoring during smartphone use in everyday life. — Nature
6. An expert-level generalist AI for abdominal CT diagnosis. — Science
7. The Sieve of Asclepius: A History of Navigating the Medical Literature, From Index to Algorithm. — Annals of Internal Medicine
8. Self-explaining artificial intelligence for the classification of B cell non-Hodgkin lymphoma: A diagnostic decision support study. — PLOS Medicine
9. Contrast-enhanced CT Radiomics for High-Grade Pattern Identification and Prognostic Stratification in Lung Adenocarcinoma with Consolidation-to-Tumor Ratio of 25% or More. — Radiology
10. Radiograph-based Deep Learning Algorithm for Assisting Bone Tumor Risk Assessment: A Multicenter Study. — Radiology

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Welcome to your weekly update in AI in Medicine.

This week's papers:

1. Generative AI-enabled clinical decision support system in primary care: a pragmatic, cluster-randomized trial. — Nature Medicine
2. An AI-Based OCT System to Detect Diabetic Macular Edema: A Prospective Validation and Noninferiority Randomized Clinical Trial. — JAMA
3. Global advances in health artificial intelligence: a workforce imperative. — The Lancet
4. Safety and security of large language models in healthcare. — Nature
5. Divergent impacts of explainable AI for dermatological diagnosis on clinicians versus lay people. — Nature Medicine
6. Health system learning enables generalist neuroimaging models. — Nature Medicine
7. An Artificial Intelligence-Enabled Cardiopulmonary Resuscitation Instructor. — JAMA Internal Medicine
8. A clinical decision support tool for accurate hip fracture prediction: A nationwide cohort study. — PLOS Medicine
9. How to benchmark medical AI agents. — PLOS Medicine
10. An ECG biomarker for sudden cardiac death discovered with deep learning. — Nature

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