A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.
View Article and Find Full Text PDFBackground: Anxiety disorders are commonly associated with a higher risk of fatal cardiovascular diseases (CVD). Anxiety disorders lead to dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, thus weakening the key neuronal components of the autonomic nervous system (ANS) that are involved in cardiovascular functions, leading to increased cardiovascular risk.
Purpose: Impaired ANS activity, as reduced parasympathetic tone is strongly associated with an increased risk of CVD in anxiety disorders.
Objective: There is conflicting evidence whether decreased clerkship duration is associated with reduced NBME shelf examination performance. We hypothesized that scores would remain stable for students in a shortened 2-week flipped classroom-based virtual rotation as compared to the traditional 4-week Neurology clerkship.
Background: There is conflicting evidence whether decreased clerkship duration is associated with reduced NBME shelf examination performance.