Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
A review published August 26, 2026 describes echocardiography workflows transitioning from manual acquisition and measurement to AI-driven interpretation, citing prospective evaluations where AI reduces examination time, automates measurements, and supports integrated assessments of ejection fraction, myocardial texture, and Doppler hemodynamics.
The study used machine learning on naive CD4+ TCR and naive BCR AIRR-seq repertoires to test classification of celiac disease versus controls, building on prior work linking germline HLA variation to naive repertoire composition and earlier BCR-based classification attempts.
Researchers retrospectively analyzed 134 acute pulmonary embolism cases from April 2023 to March 2024, using commercial AI software to automatically measure a new biomarker, pulmonary artery-to-vein volume difference, alongside traditional CTPA parameters to stratify high/intermediate-high versus lower risk.
A study tested YOLO-based AI models for breast lesion detection on digital breast tomosynthesis using a 94-patient Western database from the Cancer Imaging Archive and a 157-patient Eastern database from a single medical center, with lesions grouped into six types.
Published 25 April 2025, this peer-reviewed case study examines Roblox as a child-focused Metaverse platform, analyzing why automated and human moderation struggles with real-time interactions and massive volumes of user-generated content and documenting failures that left young users exposed to inappropriate content and predatory risks.
Published April 2, 2025 in Nature Communications, this Perspective examines how machine learning is being integrated into decentralized point-of-care testing platforms, including lateral flow, vertical flow, nucleic acid amplification, and imaging-based sensors, following a pandemic-driven shift away from centralized labs.
This review describes the rapid development of large language models such as GPT-4 and their growing use in medicine. By May 2025, the authors state that LLMs have been gradually implemented in clinical practice, medical research, and medical education, while still facing challenges of hallucination, interpretability, and ethics.
In four preregistered experiments with 4,439 participants, researchers tested how people who use AI tools at work are perceived. They found that AI users expect to be judged negatively and that observers do rate them lower on competence and motivation, with those judgments spilling over into hiring-related assessments.
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