From knowledge silos to integrated insights: building a cardiovascular medication knowledge graph for enhanced medication knowledge retrieval, relationship discovery, and reasoning.

Background: Cardiovascular diseases are diverse, intersecting, and characterized by multistage complexity. The growing demand for personalized diagnosis and treatment poses significant challenges to clinical diagnosis and pharmacotherapy, increasing potential medication risks for doctors and patients. The Cardiovascular Medication Guide (CMG) demonstrates distinct advantages in managing cardiovascular disease, serving as a critical reference for front-line doctors in prescription selection and treatment planning.

Advancing cardiac MRI multi-structure segmentation: A semi-supervised multidimensional consistency constraint learning network.

Background: Deep convolutional neural networks (DCNNs) have been proposed for medical Magnetic Resonance Imaging (MRI) segmentation, but their effectiveness is often limited by challenges in semantic discrimination, boundary delineation, and spatial context modeling.

Purpose: To address these challenges, we present the Multidimensional Consistency Constraint Learning Network (MDCC-Net) for multi-structure segmentation of cardiac MRI using a semi-supervised approach.

Methods: MDCC-Net incorporates a shared encoder, multiple differentiated decoders, and leverages pyramid boundary consistency features and spatial consistency constraints.

Detection and Evaluation for High-Quality Cardiopulmonary Resuscitation Based on a Three-Dimensional Motion Capture System: A Feasibility Study.

High-quality cardiopulmonary resuscitation (CPR) and training are important for successful revival during out-of-hospital cardiac arrest (OHCA). However, existing training faces challenges in quantifying each aspect. This study aimed to explore the possibility of using a three-dimensional motion capture system to accurately and effectively assess CPR operations, particularly about the non-quantified arm postures, and analyze the relationship among them to guide students to improve their performance.