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Background: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
View Article and Find Full Text PDFDigital Home-Based Self-Monitoring System for People with Heart Failure: Protocol for Development of SmartHeart and Evaluation of Feasibility and Acceptability.
JMIR Res Protoc
January 2025
School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Burwood, Australia.
Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.
View Article and Find Full Text PDFDO-GMA: An End-to-End Drug-Target Interaction Identification Framework with a Depthwise Overparameterized Convolutional Network and the Gated Multihead Attention Mechanism.
J Chem Inf Model
January 2025
Geneis (Beijing) Co. Ltd., Beijing 100102, China.
Identification of potential drug-target interactions (DTIs) is a crucial step in drug discovery and repurposing. Although deep learning effectively deciphers DTIs, most deep learning-based methods represent drug features from only a single perspective. Moreover, the fusion method of drug and protein features needs further refinement.
View Article and Find Full Text PDFTraining Load, Official Match Locomotor Demand, and Their Association in Top-Class Soccer Players During a Full Competitive Season.
J Strength Cond Res
February 2025
MilanLab Research Department, A.C. Milan S.p.A., Milan, Italy.
Riboli, A, Nardi, F, Osti, M, Cefis, M, Tesoro, G, and Mazzoni, S. Training load, official match locomotor demand, and their association in top-class soccer players during a full competitive season. J Strength Cond Res 39(2): 249-259, 2025-To examine training load and official match locomotor demands of top-class soccer players during a full competitive season and to evaluate their association.
View Article and Find Full Text PDFPurpose: Although publicly available cancer-related information online and offline could help patients make informed decisions, it also poses challenges due to prevalent misinformation. Patients need proper provider guidance to ensure they use valid and relevant information in decisions. We identify effective communication approaches for providers when (1) discussing patient-identified information and (2) disagreeing with it.
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