Latest AI and machine learning research in primary care for healthcare professionals.
BACKGROUND: Immune checkpoint inhibitors (ICI) improve cancer outcomes but are associated with increased atherosclerotic cardiovascular risk. Opportunistic coronary artery calcium (CAC) assessment from routine non-gated computed tomography (CT) using artificial intelligence (AI) may enable rapid cardiovascular risk stratification in this population. We evaluated the association between AI-derived ...
Urinary extracellular vesicles (uEVs) provide noninvasive biomarkers for liquid biopsy owing to their ability to reflect disease-associated molecular alterations. However, the accurate analysis of low-abundance uEV surface proteins in complex biological matrices remains a major analytical challenge. Here, we report a proximity-activated dual-cascade (PADC) biosensing platform that integrates a tar...
PURPOSE OF REVIEW: People with HIV (PWH) are increasingly susceptible to excess weight gain and obesity after initiation of antiretroviral therapy. Ho...
OBJECTIVE: To compare reading time, cancer detection rate (CDR), and abnormal interpretation rate (AIR) between AI-assisted and non-AI-assisted period...
OBJECTIVES: The sensitivity of mammographic screening is lower for women with mammographically dense vs fatty breasts. We aimed to explore automated m...
INTRODUCTION AND AIMS: Interpreting condylar osseous changes on CBCT is challenging for general practitioners. This study evaluated the 'zero-shot' di...
Chronic Kidney Disease (CKD) is a global public health crisis, affecting over 800 million people worldwide. Driven primarily by diabetes and hypertens...
BACKGROUND: Crisis helplines are a vital component of a robust public health approach to suicide prevention as they are often free, accessible, and pr...
BACKGROUND: Despite the effectiveness of lifestyle multidisciplinary (LMD) weight loss interventions in pediatric obesity, outcomes remain variable be...
Diagnostic errors are a substantial source of patient harm. As artificial intelligence (AI) integrates into clinical workflows, opportunities are emer...
OBJECTIVE: To examine how algorithmic fairness is measured, operationalized, and reported in machine learning (ML) models designed to predict or suppo...
OBJECTIVE: Stress and obesity are major health concerns affecting individuals worldwide. Artificial Intelligence (AI) is being designed to identify an...
Cardiovascular disease remains a major global health burden. Owing to its complex pathogenesis and marked clinical heterogeneity, conventional one-siz...
Although applications in the field of Robotic Technologies for Older Adults' Healthcare are becoming increasingly widespread, existing research has la...
BACKGROUND: Traditional risk factors do not fully account for the residual cardiometabolic risk of major adverse cardiovascular events (MACE) in coron...
Objective.Radiation pneumonitis (RP) is an important toxicity following breast radiotherapy. Although modern treatment techniques limit lung exposure,...
Background: Imaging-based breast cancer risk prediction models primarily use full-field digital mammography (FFDM). Although digital breast tomosynthe...
IMPORTANCE: Suicide is the leading cause of death among active-duty US Army soldiers. Evidence-based preventive interventions exist but need to be tar...
Integrating proteomic and metabolomic data is essential for understanding complex diseases, yet current approaches that rely primarily on statistical ...
Epilepsy affects roughly 50 million people worldwide and is diagnosed primarily through electroencephalography (EEG), yet the manual review on which t...