Artificial Intelligence Medical Compendium

Trifluoroacetic acid (TFA), an ultra-short-chain PFAS, is an increasingly widespread contaminant formed partly through atmospheric transformation of fluorinated replacement compounds. However, the relative roles of atmospheric deposition and hydrolog... read more 

Brain-Computer Interface (BCI) is an innovative tool that interprets brain instructions and enables humans for using their mental instructions to operate computers, robots, and other external equipment. People with motor disabilities may now utilize ... read more 

Cellular senescence, characterized by irreversible cell cycle arrest and the acquisition of a senescence-associated secretory phenotype (SASP), is a fundamental hallmark of aging and a key driver of numerous age-related diseases. However, conventiona... read more 

OBJECTIVES: To develop a fully automated multi-stage registration framework for temporomandibular joint (TMJ) imaging that enables spatial alignment between large-field-of-view cone-beam computed tomography (CBCT) and multi-planar small-field-of-view... read more 

BACKGROUND: Low- and middle-income countries (LMICs), particularly Sub-Saharan Africa, experience a high burden of surgical disease and a disproportionately high postoperative morbidity and mortality. Although machine learning based pediatric surgica... read more 

Implementation of guideline-informed care for the prevention, detection, and management of kidney disease remains suboptimal throughout the world. In November 2025, Kidney Disease: Improving Global Outcomes (KDIGO) held a Controversies Conference on ... read more 

BACKGROUND: Objective sleep and autonomic measures may add information beyond clinical characteristics when distinguishing adolescents with recent suicidal behavior. We evaluated multimodal machine-learning models for concurrent discrimination of rec... read more 

Repetitive transcranial magnetic stimulation (rTMS) is resource-intensive, and prognostic models may estimate remission probability after treatment in treatment-resistant depression (TRD). Whether algorithmic complexity improves remission prediction ... read more 

PURPOSE: To predict disease clinical course in central serous chorioretinopathy (CSC) using an interpretable machine learning model applied to baseline artificial intelligence (AI)-derived optical coherence tomography (OCT) biomarkers acquired at fir... read more 

OBJECTIVES: To assess the quality and reliability of French-language YouTube videos on induction of labour, and to investigate whether their quality is related to their popularity. METHODS: Descriptive cross-sectional study conducted from May to Augu... read more