Computer methods and programs in biomedicine
Apr 20, 2025
BACKGROUND: Diabetes mellitus, characterized by chronic glucose dysregulation, significantly increases the risk of neurological disorders such as cognitive decline, seizures, and Alzheimer's disease. As neurons depend on glucose for energy, fluctuati...
Diabetes is a growing global health concern, affecting millions and leading to severe complications if not properly managed. The primary challenge in diabetes management is maintaining blood glucose levels (BGLs) within a safe range to prevent compli...
BACKGROUND: Predicting the prognosis of patients with acute myocardial infarction (AMI) combined with diabetes mellitus (DM) is crucial due to high in-hospital mortality rates. This study aims to develop and validate a mortality risk prediction model...
Chronic disease (CD) like diabetes and stroke impacts global healthcare extensively, and continuous monitoring and early detection are necessary for effective management. The Metaverse Environment (ME) has gained attention in the digital healthcare e...
BACKGROUND: Virtual patients (VPs) are computer screen-based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.
This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney injury (AKI) in diabetic patients with heart failure (HF) during hospitalization. Using data from 1,457 patients in the MIMIC-IV database, the study ide...
Diabetes is a global health crisis with rising incidence, mortality, and economic burden. Traditional markers like HbA1c are insufficient for capturing short-term glycemic fluctuations, leading to the need for more precise metrics such as Glucose Var...
To prevent chronic disease from getting worse, it is important to detect and predict it at an early stage. Therefore, the accuracy of the prediction is particularly important. To investigate the accuracy of different methods, this study compares the ...
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