AIMC Topic: Diabetes Mellitus
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KEM-IoMT: Knowledge graph embedding-enhanced accurate medical service recommendation against diabetes.
Computers in biology and medicine
Jun 13, 2025
The Internet of Medical Things (IoMT)-enhanced Recommender System (RS) acquired swift advancement in configuring diverse medical data into intelligent systems to generate personalized medical services. However, due to the heterogeneous and complex na...
Chemical Properties-Based Deep Learning Models for Recommending Rational Daily Diet Combinations to Diabetics Through Large-Scale Virtual Screening of α-Glucosidase Dietary-Derived Inhibitors and Verified In Vitro.
Journal of agricultural and food chemistry
Jun 5, 2025
The lack of suitable chemical research methodologies has hindered the discovery of rational daily diet combinations from large-scale dietary-derived compounds. Three deep learning models based on chemical properties for α-glucosidase inhibitors (AGIs...
Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.
Scientific reports
Jun 2, 2025
Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy, neuropathy, foot problems, heart attacks, and strokes if left unchecked. Prompt detection and diagn...
Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.
Scientific reports
Jun 2, 2025
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for use is often hindered by dataset shift, which refers to discrepancies in data distribution between th...
Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development.
JMIR medical informatics
Jun 2, 2025
BACKGROUND: Diabetes affects millions worldwide. Primary care physicians provide a significant portion of care, and they often struggle with selecting appropriate medications.
Global research trends in AI-assisted blood glucose management: a bibliometric study.
Frontiers in endocrinology
May 28, 2025
BACKGROUND: AI-assisted blood glucose management has become a promising method to enhance diabetes care, leveraging technologies like continuous glucose monitoring (CGM) and predictive models. A comprehensive bibliometric analysis is needed to unders...
Cost-effectiveness of the 3E model in diabetes management: a machine learning approach to assess long-term economic impact.
Frontiers in public health
May 23, 2025
BACKGROUND: This study investigated the cost-effectiveness and clinical impact of the 3E model (education, empowerment, and economy) in diabetes management using advanced machine learning techniques.
Multitask learning multimodal network for chronic disease prediction.
Scientific reports
May 3, 2025
Chronic diseases are a critical focus in the management of elderly health. Early disease prediction plays a vital role in achieving disease prevention and reducing the associated burden on individuals and healthcare systems. Traditionally, separate m...
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...
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