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Artificial Intelligence-Enabled Electrocardiogram Predicts Sudden Cardiac Death in Repaired Tetralogy of Fallot.
JACC Clin Electrophysiol
January 2025
Department of Cardiology, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA. Electronic address:
Age, creatinine, and ejection fraction score is a risk factor for acute kidney injury after surgical aortic valve replacement.
Ren Fail
December 2025
Center for Cardiac Intensive Care, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China.
Background: The incidence of acute kidney injury (AKI) increases after surgical aortic valve replacement (SAVR). This study aimed to characterize the risk factors of AKI after SAVR.
Methods And Results: We conducted a retrospective registry study based on data from 299 consecutive patients undergoing SAVR.
MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks.
BMC Bioinformatics
January 2025
Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing Anzhen Hospital of Capital Medical University, Beijing, 101100, China.
Background: MicroRNAs (miRNAs) are pivotal in the initiation and progression of complex human diseases and have been identified as targets for small molecule (SM) drugs. However, the expensive and time-intensive characteristics of conventional experimental techniques for identifying SM-miRNA associations highlight the necessity for efficient computational methodologies in this field.
Results: In this study, we proposed a deep learning method called Multi-source Data Fusion and Graph Neural Networks for Small Molecule-MiRNA Association (MDFGNN-SMMA) to predict potential SM-miRNA associations.
The 2024 Nobel Prizes: AI and Computational Science Takes Center Stage.
J Allergy Clin Immunol
January 2025
National Heart and Lung Institute, Imperial College London, UK; NIHR Imperial Biomedical Research Centre, UK; Frankland and Kay Allergy Centre, Imperial College London, UK.
The Omics-Driven Machine Learning Path to Cost-Effective Precision Medicine in Chronic Kidney Disease.
Proteomics
January 2025
School of Public Health, University of Haifa, Haifa, Israel.
Chronic kidney disease (CKD) poses a significant and growing global health challenge, making early detection and slowing disease progression essential for improving patient outcomes. Traditional diagnostic methods such as glomerular filtration rate and proteinuria are insufficient to capture the complexity of CKD. In contrast, omics technologies have shed light on the molecular mechanisms of CKD, helping to identify biomarkers for disease assessment and management.
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