Artificial Intelligence Medical Compendium

RATIONALE AND OBJECTIVES: To evaluate the feasibility of a quantitative magnetic resonance imaging (MRI)-to-structured reporting pipeline that integrates quantitative MRI software with large language models (LLMs) for structured drafting of neurodege... read more 

BackgroundInadequate or misleading health information about silicosis can delay diagnosis, reporting, and exposure removal, potentially affecting risk communication and timely occupational health interventions.ObjectiveThis study evaluates the reliab... read more 

BACKGROUND: Obesity's global rise has outpaced the effectiveness of "one-size-fits-all" prevention and treatment strategies. The promise of precision medicine lies in addressing the etiological and biological diversity of obesity and transforming it ... read more 

Solid electrolytes (SEs) are central to next-generation metal batteries, yet their discovery remains constrained by fragmented data, limited transferability of simulations, and slow experimental iteration. Unlike catalysis, where surface reactivity d... read more 

Pain is a multifaceted sensory and emotional experience that profoundly affects human health and quality of life. It functions as a double-edged sword: while acute pain serves as a protective warning signal, chronic pain compromises physiological and... read more 

OBJECTIVE: Health economic models (HEMs) are crucial for assessing the cost-effectiveness of healthcare interventions, informing policy decisions and guiding reimbursement strategies. This study examines the feasibility of employing generative artifi... read more 

MOTIVATION: Gene function prediction is pivotal in genomic and metagenomic data analysis. Current annotation tools typically rely on the most similar sequence from the query database and struggle to robustly set meaningful hit thresholds, causing a m... read more 

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BACKGROUND: Machine learning (ML) is increasingly used for sarcopenia screening, but its added value over conventional models remains uncertain when datasets are moderately sized and predictors are few. We compared logistic regression (LR) with five ... read more 

BACKGROUND: Artificial intelligence (AI)/machine learning (ML) are poised to transform transfusion medicine across the vein-to-vein continuum, from donor recruitment to recipient outcomes. Large datasets generated from millions of donations and trans... read more