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A purpose-driven video game can improve triage of elderly trauma patients.
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Using Serious Games to Increase the Implementation of Trauma Triage Guidelines: A Randomized Clinical Trial. JAMA. 2026 May 19;335(19):1672-1683. doi: 10.1001/jama.2026.4079. PMID: 42008277; PMCID: PMC13097024.
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In a large multicenter ICU study, five different pulse oximeter models overestimated oxygen saturation in patients with darker skin tones, leading to substantially higher false negative rates for hypoxemia.
Source
EXAKT Study Investigators. The impact of skin tone on performance of pulse oximeters used by NHS England COVID Oximetry @home scheme: measurement and diagnostic accuracy study. BMJ. 2026 Jan 14;392:e085535. doi: 10.1136/bmj-2025-085535. PMID: 41534914; PMCID: PMC12801414.
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In this prospective study of critically ill and cardiac arrest patients, an AI tool demonstrated high accuracy for predicting blood pressure based on carotid ultrasound imaging.
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AI-driven carotid artery compressibility assessment via point-of-care ultrasound for blood pressure estimation in critically ill and post-resuscitation patients: a prospective observational study. Crit Care. 2025 Nov 28;30(1):2. doi: 10.1186/s13054-025-05772-2. PMID: 41316299; PMCID: PMC12764074.
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Using EHR data from the first 4 hours of ED care, machine learning models accurately predicted which children would develop sepsis within 48 hours—before organ dysfunction was present.
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Derivation and Validation of Predictive Models for Early Pediatric Sepsis. JAMA Pediatr. 2025 Dec 1;179(12):1318-1325. doi: 10.1001/jamapediatrics.2025.3892. PMID: 41082207; PMCID: PMC12519407.
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Implementing voice recognition (VR) software for dictating electronic health record (EHR) notes in the ED enhances efficiency by streamlining documentation processes.
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Observational service evaluation of voice recognition technology in the emergency department: association with electronic note-writing efficiency. Emerg Med J. 2025 Sep 25:emermed-2024-214589. doi: 10.1136/emermed-2024-214589. Epub ahead of print. PMID: 40998570.
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A well-codified approach to AI research, regulatory oversight, and implementation practices is currently lacking. This JAMA summit report level-sets the key promises, pitfalls, and priorities for AI in medicine.
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AI, Health, and Health Care Today and Tomorrow: The JAMA Summit Report on Artificial Intelligence. JAMA. 2025 Oct 13. doi:10.1001/jama.2025.18490. Epub ahead of print. PMID: 41082366.
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After 48 hours of brain rest, moderate recreational screen time may support better psychological recovery post-concussion compared to restrictive or excessive use.
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Effects of Screen Time Use on Psychological Symptoms in Adolescents Following Concussion. J Neurotrauma. 2025 Sep 30. doi: 10.1177/08977151251385568. Epub ahead of print. PMID: 41027657.
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Reliance on STEMI criteria alone misses a substantial proportion of LAD occlusions, while expert and AI ECG interpretation achieved earlier and more accurate detection, with 100% sensitivity for LAD occlusion MI in this study.
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Failure of standard contemporary ST-elevation myocardial infarction electrocardiogram criteria to reliably identify acute occlusion of the left anterior descending coronary artery. Eur Heart J Acute Cardiovasc Care. 2025 Aug 6;14(7):403-411. doi: 10.1093/ehjacc/zuaf037. PMID: 40717627.
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The Queen of Hearts AI (QoH AI) model beat both emergency physicians (EPs) and cardiologists at deciding who needs immediate catheterization for certain STEMI-equivalents and STEMI-mimics—88.9% accuracy vs. ~66%—promising fewer missed occlusion myocardial infarctions (OMIs) and fewer unnecessary activations.
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Accuracy of cath lab activation decisions for STEMI-equivalent and mimic ECGs: Physicians vs. AI (Queen of Hearts by PMcardio). Am J Emerg Med. 2025 Jul 30;97:193-199. doi: 10.1016/j.ajem.2025.07.061. Epub ahead of print. PMID: 40763602.
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Comparing the accuracy of ECG interpretation between Emergency Medicine Providers (EMP) and 3 separate AI models, EMPs narrowly took the lead.
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Task-specific versus general-purpose AI models in ECG analysis: A comparative study with emergency medicine specialists. Am J Emerg Med. 2025 Sep;95:220-226. doi: 10.1016/j.ajem.2025.06.068. Epub 2025 Jun 27. PMID: 40609173