BACKGROUND: The integration of artificial intelligence (AI) into clinical practice is contingent on public trust. This trust often depends on physician oversight, yet a significant gap exists between the need for AI-competent physicians and the curre... read more
The existence of sex differences in human pre-implantation development remains an open question, with previous attempts based on human observations yielding inconclusive results. In this study, we combined manual annotation and deep learning analysis... read more
Objective: To identify and compare predictors of nonfatal and fatal suicidal events within 180 days of emergency department (ED) visits for mental health disorders. Methods: This longitudinal cohort analysis assessed risk of nonfatal and fatal suicid... read more
Infectious diseases (IDs) pose a significant global health threat, exacerbated by the rise of multidrug-resistant (MDR) and antimicrobial-resistant (AMR) pathogens. The conventional diagnostic methods, such as culture characteristics, microscopical e... read more
OBJECTIVE: This study aims to develop an advanced clinical event prediction model leveraging the temporal characteristics embedded within electronic health record (EHR), with a specific focus on predicting clinical events during the hospitalization o... read more
The global burden of Parkinson's disease (PD) is projected to double by 2050, with early-onset cases demonstrating accelerated progression and limited therapeutic options. Recently, carbon quantum dots (CQDs) emerge as promising nanoplatforms for PD ... read more
OBJECTIVE: In hypertrophic cardiomyopathy (HCM), detection of coronary microcirculatory dysfunction (CMD) usually relies on contrast-enhanced cardiac magnetic resonance (CMR). This study sought to develop a practical non-contrast radiomics model to i... read more
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