Latest AI and machine learning research in primary care for healthcare professionals.
Background Gestational diabetes mellitus (GDM) affects 1-in-7 pregnancies globally and is associated with significant short- and long-term health consequences. Although health behaviour change interventions can effectively reduce these risks, a significant implementation gap exists in translating this evidence into routine practice. Bump2Baby and Me (B2B&Me) was a mobile health (mHealth) coaching ...
Agentic research systems are emerging as a new paradigm for coordinating scientific workflows beyond isolated model inference, code generation, or statistical analysis. However, deployment in institutional biomedical environments requires governed mechanisms for research planning, data access, workflow orchestration, evidence tracking, reproducibility, and human oversight. We present NVAITC AI Sci...
Accurate breast cancer risk prediction from screening mammography is critical for enabling personalized screening intervals and early detection. Recen...
Background: Nuclear medicine and radiopharmaceutical development require coordinated radiochemistry, dosimetry, molecular imaging, radiation-safety an...
Background: Hypertension is a modifiable risk factor for dementia, yet the comparative effectiveness of angiotensin receptor blockers (ARBs) versus an...
Abstract Climate change is altering environmental conditions that influence foodborne disease transmission, yet traditional systematic reviews cannot ...
Directed evolution consisting of iterative rounds of diversification, selection, and counter-selection, underlies modern protein and antibody engineer...
Background Hypercapnia may indicate a primary ventilatory syndrome, a complication of another illness, or an epiphenomenon of severe disease. The pres...
Abstract Background: Lacunes are 3-15 mm cavities originating from small perforating artery disease and are a hallmark of cerebral small vessel diseas...
Background: Coronary artery calcium (CAC) is an established measure of coronary atherosclerosis from computed tomography (CT). While deep learning (DL...
Background: Poor glycemic control is associated with cardiovascular disease (CVD) risk. However, it is unknown whether glycemic control is related to ...
Depression screening from large-scale behavioral data is challenged by fragmented circadian indicators, limited interpretability, and the lack of inte...
Modern GPU domain-specific languages (DSLs), such as Triton and TileLang, are increasingly used to implement specialized deep-learning kernels and as ...
Background: Despite advances in circulating tumor DNA analysis, reliable detection of oncological disease from ultra-low coverage whole genome sequenc...
Screening therapeutic candidates from single-cell transcriptomes requires a target that is closer to treatment response than disease-signature reversa...
Introduction. Systematic reviews are essential for informing health policy and practice. Artificial intelligence (AI) automates the article screening ...
While Photoplethysmography (PPG) is established as a noninvasive optical tool for monitoring heart rate and oxygen saturation, its high-resolution blo...
INTRODUCTION: Accurate MRI-based identification of Alzheimer's disease (AD), mild cognitive impairment (MCI), and related dementias remains challengin...
Ground reaction force (GRF)-based gait analysis provides objective, non-invasive evidence for neurological and musculoskeletal assessment, but its tra...
Background: Rare diseases affect a significant portion of the global population, yet patients often endure a lengthy diagnostic odyssey, frequently mi...