Routine Blood Test Model Identifies Heart Failure in Patients With COPD
A machine learning model trained on routine laboratory tests identified comorbid heart failure in patients with chronic obstructive pulmonary disease.
A machine learning model trained on routine laboratory tests identified comorbid heart failure in patients with chronic obstructive pulmonary disease.
A comprehensive clinical review details how specialized preoperative evaluation and targeted comorbidity optimization significantly improve postoperative outcomes and reduce perioperative ...
A study evaluating combined mouse genetic reference populations found that merging divergent panels yielded fewer significant association loci than one ...
A multi-omics analysis of peripheral blood from heart failure patients reveals shared genomic variants, downregulated expression signatures, and convergent mechanoinflammatory ...
A post hoc analysis of an international survey reveals that specific debilitating symptoms and the loss of daily functional independence ...
A two-sample Mendelian randomization study indicates that genetically predicted body mass index and smoking initiation liability are significantly associated with ...
Researchers showed that Shenfu Qiangxin pill alleviates heart failure with preserved ejection fraction in mice by reprogramming dysregulated macrophage, fibroblast, ...
In a prospective study of Kenyan heart failure patients, non-contrast echocardiography demonstrated an excellent negative predictive value for excluding left ...
A systematic review found that existing risk prediction models for late-onset cancer therapy-related cardiac dysfunction are largely limited by bias ...
UVA researchers are developing an AI tool called GenStrain with a $4 million NIH grant to personalize heart failure pacing ...
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© 2026 Scienmag - Science Magazine