Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...
Background Percutaneous ventricular assist devices (pVAD) have been increasingly used to support haemodynamics during ...
Background Recent cardiovascular risk equations from the USA and United Kingdom use routinely collected electronic medical records (EMRs), while current equations used in Australia (AusCVDRisk) have ...
This important study describes a deep learning framework that analyzes single-cell RNA data to identify a tumor-agnostic gene signature associated with brain metastases. The identified signature ...
Objective Lupus nephritis (LN) is a prevalent renal manifestation in patients with SLE, with kidney biopsy remaining the gold ...
Objectives Heart failure (HF), chronic kidney disease (CKD) and atherosclerotic cardiovascular disease (ASCVD) are highly prevalent conditions that often coexist. Using electronic health records (EHRs ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...
Suzanne is a content marketer, writer, and fact-checker. She holds a Bachelor of Science in Finance degree from Bridgewater State University and helps develop content strategies. Regression analysis ...
This manuscript makes a valuable contribution to understanding learning in multidimensional environments with spurious associations, which is critical for understanding learning in the real world. The ...
Although some outcomes showed small to medium effect sizes, these results must be interpreted cautiously given the presence ...
Time-to-event is a powerful statistical approach increasingly used in sports science and medicine to examine time-to-event outcomes such as time to sports injury occurrence, career duration and ...
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