Artificial Intelligence Medical Compendium

Cardiac motion artifacts frequently degrade the quality and interpretability of coronary computed tomography angiography (CCTA) images, making it difficult for radiologists to identify and evaluate the details of the coronary vessels accurately. In t... read more 

This study aims to develop and assess an optimized three-dimensional convolutional neural network model (3D CNN) for predicting major cardiac events from coronary computed tomography angiography (CCTA) images in patients with suspected coronary arter... read more 

Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect disease processes. Recent advances in high-throughput spatial omics technologies have enabled the inv... read more 

BackgroundNecrotizing enterocolitis (NEC) is an intestinal ischemic disease that affects preterm infants with fetal growth restriction (FGR). The role of fetal Dopplers in stratifying risk for developing NEC is unclear but the innovative use of machi... read more 

PURPOSE: The purpose of this study was to evaluate the relationship between structural abnormalities on CT and lung function prior to and after initiation of elexacaftor-tezacaftor-ivacaftor (ETI) in adults with cystic fibrosis (CF) using a deep lear... read more 

OBJECTIVE: Failure to rescue (FTR) is a significant quality indicator for postoperative cardiothoracic care. We developed an interpretable artificial intelligence model to identify, interpret, and integrate patient risk factors to predict FTR after c... read more 

BACKGROUND: To develop an artificial intelligence-based predictive model using ankle-brachial index (ABI) dynamic fluctuation patterns and evaluate its predictive value for major adverse limb events (MALEs) in patients with peripheral arterial diseas... read more 

INTRODUCTION: Honey bees are essential managed pollinators faced by nutritional deficiencies which contributes to worldwide colony losses. The integration of nutrition science with genomics offers a powerful approach to optimize honey bee health by a... read more 

Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks, and reliance on specialized infrastructure limit accessibility and scalability of standard-of-care... read more 

Accurate prognostic stratification is essential for optimizing postoperative therapeutic strategies in oncology. While deep learning approaches have shown promise for survival prediction through unimodal analyses of histopathological images, transcri... read more