AIMC Topic: Diabetes Mellitus
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Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.
Lipids in health and disease
Apr 29, 2025
BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular risks. Novel obesity indices, such as the body roundness index (BRI), conicity index, and relative ...
Managing chronic disease in the digital era: The role of telemedicine apps and platforms.
Przeglad epidemiologiczny
Apr 28, 2025
Chronic diseases such as diabetes, heart disease, or asthma are one of the biggest health challenges of the modern world. Their management requires constant care and monitoring, which is a serious burden for healthcare systems. In the digital era, th...
Computational modelling for risk assessment of neurological disorder in diabetes using Hodgkin-Huxley model.
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: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.
Biosensors
Apr 16, 2025
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...
Machine learning for high-risk hospitalization prediction in outpatient individuals with diabetes at a tertiary hospital.
Archives of endocrinology and metabolism
Apr 15, 2025
OBJECTIVE: To characterize, via a predictive model using real-world data, patients with diabetes with a heightened probability of hospitalization.
Predicting diabetes mellitus metabolic goals and chronic complications transitions-analysis based on natural language processing and machine learning models.
PloS one
Apr 15, 2025
OBJECTIVE: To estimate Diabetes mellitus (DM) progression at one and two years in terms of glycemic targets and development of complications.
Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mellitus.
Acta cardiologica
Apr 8, 2025
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...
An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment.
Scientific reports
Apr 4, 2025
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...
Virtual Patients Using Large Language Models: Scalable, Contextualized Simulation of Clinician-Patient Dialogue With Feedback.
Journal of medical Internet research
Apr 4, 2025
BACKGROUND: Virtual patients (VPs) are computer screen-based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.
Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.
Scientific reports
Mar 28, 2025
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...
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