JAMA+ AI @JAMAplusAI
JAMA+ AI is a window into the scientific content, educational reviews, and commentary on AI & medicine published across the @JAMANetwork family of journals. JAMAai.org Chicago, IL Joined September 2024-
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💬 Editor's Note by JAMA Deputy Editors Preeti Malani, MD, MSJ, and Joseph Ross, MD, MHS: As generative #AI tools become more advanced and accessible, transparent reporting and updated editorial guidance are needed to ensure research integrity. ja.ma/4wBdEwx
In the latest episode of the #healthyDialogue podcast, JAMA Senior Editor Derek Angus, MD, MPH, and Vincent Liu, MD, MS, discuss the evolution of ambient #AI scribes in #health care. 🔗 ja.ma/4blN3v6
Ambient #AI scribes now #automate documentation and #clinical assessments, offering time savings and reduced burnout, but raise important questions about oversight, automation bias, and accountability. 🔗 ja.ma/4blN3v6
A deep transfer learning (#DTL) model using preimplant #MRI accurately predicted spoken language improvement in children with cochlear implants, outperforming traditional machine learning. ja.ma/3RoU73m
Self-disclosed use of #AI in research manuscripts submitted to BMJ journals rose from 4.5% to 7.3% between April and October 2024. Most disclosures related to writing improvement, and reporting varied by geographic region. ja.ma/4xfV9O8
Ambient #AI scribes increased documentation of neuropsychiatric symptoms in primary care, but were associated with lower rates of psychiatric intervention compared with unscribed visits. ja.ma/4yRAVvI
Using #InternationalClassificationofDiseases codes to predict same-admission outcomes can inflate #ArtificialIntelligence model performance because those codes may only be finalized after discharge, limiting real-time clinical use. ja.ma/3TSUfsu
💬 Viewpoint: Clinician-facing #ArtificialIntelligence medical knowledge platforms may degrade if financial incentives outweigh quality goals, supporting benchmarks, regulation, and antitrust enforcement to protect evidence-based care. ja.ma/3U8iMKa
💬 Perspective: #GenerativeAI may improve #ClinicalDecisionSupport when it synthesizes decision-relevant patient context, but outputs should remain grounded in curated sources with source attribution and deterministic verification. ja.ma/3TxMLv6
Six ED #LLMs showed similar discrimination but different sensitivity and specificity for missed #diagnosis screening, underscoring the need for cohort-specific calibration in #clinical workflows. #AI #EmergencyMedicine ja.ma/4fEv97S
Machine learning analysis of patient-clinician conversations identified cognitive impairment with sensitivity 68% and specificity 64%, supporting passive speech-based screening in routine #PrimaryCare. ja.ma/4w0ksCL
Trying to build your #AI knowledge? The JAMA+ AI Editors have curated resources to understand key concepts in AI in medicine, along with must-read AI articles from across the JAMA Network. 📌 Explore JAMA+ AI Resources: ja.ma/4vZXmx9
📊 A reasoning model is a type of #LargeLanguageModel designed to improve problem-solving by breaking complex tasks into step-by-step reasoning. JAMA+ AI Associate Editor Yulin Hswen, ScD, MPH, explains concepts in #AI that every #clinician should know. ja.ma/4gwnL0I
💬 Viewpoint: Pediatric #AI must balance timely access and rigorous safety. A child-in-the-loop framework centers consent, transparency, and equity, with strong governance for effective and ethical adoption. ja.ma/4eUoGXp
A deep transfer learning (#DTL) model using preimplant #MRI accurately predicted spoken language improvement in children with cochlear implants, outperforming traditional machine learning. ja.ma/3RaVuSO
💬 Invited Commentary: A machine learning model surpassed UCAS and PHASES scores in predicting intracranial aneurysm rupture, especially for small aneurysms, with morphology as the key predictor. ja.ma/4f7P5Qr
In this episode of JAMA+ AI Conversations, Roy Perlis, MD, MSc, and Yulin Hswen, ScD, MPH, discuss Anthropic's participation in the Vatican presentation of Pope Leo XIV's AI encyclical, Magnifica Humanitas. ja.ma/3TpXXcQ
🎤 JAMA+ AI Conversations: #AI use for mental health is widespread among youth, with many reporting it as helpful—but objective benefits, equity, and impacts on care, therapeutic relationships, and #clinician workflows remain uncertain. ja.ma/3TpXXcQ
🤖 What is #bias in #AI? Systematic errors in AI predictions can affect diagnoses, treatment recommendations, and medical device performance. In this explainer video, JAMA+ AI Editor in Chief Roy Perlis, MD, MSc, explains key concepts in #AI that every #clinician should know.
Self-disclosed use of #AI in research manuscripts submitted to BMJ journals rose from 4.5% to 7.3% between April and October 2024. Most disclosures related to writing improvement, and reporting varied by geographic region. jamanetwork.com/journals/jama/…
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