BACKGROUND: Artificial intelligence (AI) is reshaping healthcare, yet its integration into medical education remains limited. This study assesses undergraduate healthcare students' knowledge and perceptions of AI, its applications, challenges, and th...
OBJECTIVE: This prospective study aimed to assess the feasibility of a half-Fourier single-shot turbo spin echo sequence (HASTE) with deep learning (DL) reconstruction for ultrafast imaging of the bladder with reduced susceptibility to motion artifac...
Clozapine is an atypical antipsychotic used for patients with treatment-resistant schizophrenia. This drug has serious adverse drug reactions (ADRs), including the risk of severe neutropenia (agranulocytosis). Patients who could benefit from clozapin...
To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of venous phase using deep learning (DL) and Radiomics approaches to predict lymphovascular invasion in gastric cancer prior to surgery. We retrospectiv...
BACKGROUND: Malaysia, an upper middle-income country in the Asia-Pacific region, has an HIV epidemic that has transitioned from needle sharing to sexual transmission, mainly in men who have sex with men (MSM). MSM are the most vulnerable population f...
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...
OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic fatty liver disease (NAFLD) using the random survival forests (RSF), and to investigate the distribution of NAFLD risk with time.
Recurrent pregnancy loss (RPL), which affects approximately 2.5% of reproductive-aged women, remains idiopathic in more than 50% of cases, necessitating mechanistic insights and biomarkers. Three RPL decidual tissue transcriptomic datasets (GSE113790...
Personalized stimulation, in which algorithms used to detect neural events adapt to a user's unique neural characteristics, may be crucial to enable optimized and consistent stimulation quality for both fundamental research and clinical applications....
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