Working memory (WM) is a core cognitive mechanism necessary for adaptive behavior. In the last few decades, scientists have studied WM using rodent models through traditional and time-consuming approaches, such as the Radial Arm Maze and the T-Maze. ...
Marine bioactive peptides (MBPs) are short-chain amino acid polymers derived from marine sources that possess specific physiological activities. Owing to their unique origins and structural diversity, MBPs have attracted considerable research interes...
UNLABELLED: The study assesses the performance of AI models in evaluating postmenopausal osteoporosis. We found that ChatGPT-4o produced the most appropriate responses, highlighting the potential of AI to enhance clinical decision-making and improve ...
OBJECTIVES: To explore perceptions of digitalisation and patient safety from the view of the German general public and related sociodemographic factors.
BACKGROUND: Youth mental health issues have been recognized as a pressing crisis in the United States in recent years. Effective, evidence-based mental health research and interventions require access to integrated datasets that consolidate diverse a...
This study investigates the relationship between occupational automation risks and workers' transitions to entrepreneurship using data from the Current Population Survey. We find that employees facing automation-related job displacement are inclined ...
PURPOSE: Bronchiolar adenoma (BA) is a rare benign pulmonary neoplasm originating from the bronchial mucosal epithelium and mimics lung adenocarcinoma (LAC) both radiographically and microscopically. This study aimed to develop a nomogram for disting...
Large language models (LLMs) represent a transformative advance in artificial intelligence, with growing potential to impact chronic kidney disease (CKD) management. CKD is a complex, highly prevalent condition requiring multifaceted care and substan...
Journal of the American College of Cardiology
Sep 7, 2025
BACKGROUND: Accurate measurement of echocardiographic parameters is crucial for the diagnosis of cardiovascular disease and tracking of change over time; however, manual assessment requires time-consuming effort and can be imprecise. Artificial intel...
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, with growing interest in their application to rare pediatric surgical conditions. In these settings, limited data availability often brakes traditional resear...
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