Medicine & Health
467 items
An AI Competency Framework for Emergency Medicine: A Multiphase Consensus Process
Using a Nominal Group Technique session (May 2025, n=6) and a two-round modified Delphi process (April–May 2026, expert panel n=13 across 12 academic medical centers, with 77% Round 1 and 100% Round 2 response rates), this study developed the first specialty-specific AI competency framework for a United States medical specialty, comprising 5 themes (Communicating about AI, Understanding appropriate use cases, Interacting with AI, AI risk management, Cognitive impacts of AI), 5 derived competencies (one-to-one theme-to-competency mapping endorsed by 12 of 13 panelists), 19 subthemes, and 10 retained clinical scenarios, with all themes, derived competencies, and individually rated subthemes meeting pre-specified consensus thresholds and 9 of 10 scenarios reaching consensus while 1 was retain
Medical Device Safety Throughout the Product Lifecycle: Regulatory Frameworks, Digital Transformation, and the Role of Artificial Intelligence in Devices and Monitoring
This narrative review, based on structured searches of PubMed and ScienceDirect (2016-2026, plus a clinical-research-focused search for 2013-2026) supplemented by FDA, EMA, Cochrane Library, and industry sources, examines medical device safety across the full lifecycle from early design and clinical investigation through regulatory review, postmarket surveillance, software change management, cybersecurity, and AI/ML-enabled device oversight, arguing that device safety requires a broader socio-technical framework than drug safety and that safety evidence is shifting from retrospective, passive reporting toward proactive, real-time, lifecycle-based generation.
Liquid biopsy in glioblastoma: emerging technologies and translational opportunities
This review focuses on liquid biopsy for glioblastoma, noting that tissue biopsy is invasive and fails to capture tumor heterogeneity or temporal dynamics, while liquid biopsy can provide noninvasive real-time monitoring via circulating biomarkers such as cell-free DNA, circulating tumor DNA, circulating tumor cells, and extracellular vesicles in plasma, cerebrospinal fluid, urine, and saliva; it advances beyond prior biomarker catalogs by delivering a quantitative technology scorecard comparing cfDNA-, CTC-, and EV-based platforms in terms of sensitivity, clinical actionability, cost, and scalability, and introduces a multimodal decision matrix and an AI-driven fusion pipeline integrating fragmentomics, EV proteomics, and CTC transcriptomics to enhance minimal residual disease detection a
Current Concepts and Emerging Technologies in Aesthetic Outcome Assessment of Breast Reconstruction: A Systematic Review
This systematic review searched studies from 2000 to 2025 evaluating aesthetic outcomes after implant-based, autologous, or hybrid breast reconstruction, included 51 studies with 7711 participants from 16 countries, classified assessments as subjective or objective, found subjective tools led by BREAST-Q (35/51, 69%) and objective methods in 19 studies including 3-dimensional surface imaging (8/51, 16%), BCCT.core (7/51, 14%), eye tracking (3/51, 6%), and artificial intelligence-based analyses (3/51, 6%), and noted that no single modality comprehensively addresses all aesthetic domains, with a progressive shift toward multimodal evaluation.
Can Artificial Intelligence Deliver in Real-World Health Systems? Early Insights From AIM-HI's 5 Funded Projects
This article synthesizes early cross-project insights from the 5 projects funded by the Augmented Intelligence in Medicine and Healthcare Initiative (AIM-HI), led by Kaiser Permanente and funded by the Gordon and Betty Moore Foundation and selected through a national, multistage review process using a structured scoring rubric, covering sepsis management, venous thromboembolism risk assessment, diabetic retinopathy screening, cardiac amyloidosis detection, and pediatric asthma risk prediction; it reports that real-world AI deployment was feasible across varied clinical environments, that common challenges included electronic health record integration, data complexity, regulatory requirements, and variation in clinical workflows, and that implementation success depends on thoughtful integra
AI-assisted handheld echocardiography for hospital bedside cardiac triage: the prospective OPTIMUST implementation study
OPTIMUST was a prospective, single-center implementation study in which physicians without formal echocardiography certification completed a structured two-month curriculum and performed focused examinations using Caption AI-enabled handheld ultrasound on cardiology and non-cardiology wards; of 287 attempted examinations, 206 (71.8%) were analyzable, operator assessment correlated with expert review of the same handheld image sets for LVEF (r = 0.84), filling-pressure category agreement gave a quadratic weighted κ of 0.659, physicians reported that handheld findings changed or confirmed management in 93.7% of examinations, and 32.8% underwent comprehensive echocardiography within one month.
Epigenetic Mechanisms and Clinical Translation in Ovarian Cancer: From Molecular Pathways to Precision Therapy
This review systematically examines how DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA networks drive chemoresistance and recurrence in ovarian cancer, summarizes clinical trial results of epigenetic agents (DNMT, HDAC, and EZH2 inhibitors) combined with PARP inhibitors or immunotherapy, and reviews biomarker advances based on circulating cfDNA methylation, circulating miRNAs, and AI-based liquid biopsy platforms, proposing a precision oncology framework for patient stratification and real-time monitoring of chemoresistance.
Auditing Sex/Gender Disparities in Emergency Triage with LLM-based Paired Comparisons
The study introduces a domain-agnostic paired-comparison approach that fine-tunes a large language model to emulate documented emergency triage decisions and then compares predictions on sex-swapped pairs in which only sex is flipped while documented clinical content is held constant, finding that otherwise identical presentations were more likely to receive a lower-severity (less urgent) predicted triage score as female than male, with a pooled per-pair rate of about 1.1% (95% CI 0.9–1.3) across more than 140,000 Bordeaux University Hospital admissions and a directionally consistent but larger 2.2% (1.7–2.7) in MIMIC-IV, while a model retrained on sex-neutralized inputs eliminated the between-sex prediction gap, indicating the asymmetry is mediated by explicit sex markers.
Problematic Reliance on Generative AI in an Anxious Young Adult: A Case Report
This case report describes a woman in her mid-20s with generalized anxiety disorder and major depressive disorder and a history of strong social, academic, and occupational functioning who developed a pattern of functional dependence on ChatGPT, outsourcing routine cognitive and interpersonal tasks such as composing emails, interpreting social interactions, predicting the future, and making decisions, and becoming increasingly uncomfortable completing such tasks independently; the authors frame this as cognitive offloading, reduced confidence in independent judgment, and reinforcement of externalized thinking using the I-PACE model, and suggest that the unlimited accessibility of AI tools may intensify reassurance seeking and worsen tolerance of uncertainty.
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