AIMC Topic: Diabetes Mellitus, Type 2
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Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.
Nutrients
Mar 8, 2025
: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM ...
Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.
Gut microbes
Mar 6, 2025
Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between the functional capacity of gut microbiota and their host remains elusive for DKD. This study aims to elucidate the functional capability of gut microbio...
Yi-qi-yang-yin decoction ameliorates diabetic retinopathy: New and comprehensive evidence from network pharmacology, machine learning, molecular docking and molecular biology experiment.
Journal of pharmaceutical and biomedical analysis
Mar 6, 2025
Yi-Qi-Yang-Yin Decoction (YQYY), a traditional Chinese medicine (TCM) formula, has been used to treat diabetic retinopathy (DR), yet its precise mechanisms of action remain poorly understood. In this study, two distinct diabetic models, namely sponta...
Diabetes Mellitus, Type 2
Diabetic Retinopathy
Mice
Machine Learning
Drugs, Chinese Herbal
Animals
Rats
Medicine, Chinese Traditional
Chromatography, High Pressure Liquid
Diabetes Mellitus, Experimental
Signal Transduction
Male
Rats, Sprague-Dawley
Network Pharmacology
Molecular Docking Simulation
Mice, Inbred C57BL
Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses.
BMC medical informatics and decision making
Mar 6, 2025
INTRODUCTION: Cellular Communication Network Factor 6 (CCN6) is an adipokine whose production undergoes significant alterations in metabolic disorders. Given the well-established link between obesity-induced adipokine dysfunction and the development ...
Two-step pragmatic subgroup discovery for heterogeneous treatment effects analyses: perspectives toward enhanced interpretability.
European journal of epidemiology
Mar 4, 2025
Effect heterogeneity analyses using causal machine learning algorithms have gained popularity in recent years. However, the interpretation of estimated individualized effects requires caution because insights from these data-driven approaches might b...
Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysis.
Frontiers in endocrinology
Mar 3, 2025
BACKGROUND: Machine learning (ML) models are being increasingly employed to predict the risk of developing and progressing diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). However, the performance of these models still ...
Artificial intelligence based predictive tools for identifying type 2 diabetes patients at high risk of treatment Non-adherence: A systematic review.
International journal of medical informatics
Mar 1, 2025
AIMS: Several Artificial Intelligence (AI) based predictive tools have been developed to predict non-adherence among patients with type 2 diabetes (T2D). Hence, this study aimed to describe and evaluate the methodological quality of AI based predicti...
Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning.
Scientific reports
Feb 25, 2025
To analyze radiomics features of cardiac adipose tissue in individuals with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD), integrating relevant clinical indicators, and employing machine learning techniques to construct a preci...
SERPINA3: A Novel Therapeutic Target for Diabetes-Related Cognitive Impairment Identified Through Integrated Machine Learning and Molecular Docking Analysis.
International journal of molecular sciences
Feb 24, 2025
Diabetes-related cognitive impairment (DCI) is a severe complication of type 2 diabetes mellitus (T2DM), with limited understanding of its molecular mechanisms hindering effective therapeutic development. This study identified SERPINA3 as a potential...
Food-derived DPP4 inhibitors: Drug discovery based on high-throughput virtual screening and deep learning.
Food chemistry
Feb 21, 2025
Dipeptidyl peptidase-4 (DPP-4) is a critical target for the treatment of type 2 diabetes. This study outlines the development of six compounds derived from food sources and modified to create promising candidates for the treatment of diabetes. These ...
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