AIMC Topic: Diabetes Mellitus, Type 2
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Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.
Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2025
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...
Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning.
Scientific reports
May 25, 2025
Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus. Identifying who is most at risk remains challenging due to the non-linear relationships between hypoglycemia and its associated risk factors. The objective of this s...
Integrating bioinformatics and machine learning to unravel shared mechanisms and biomarkers in chronic obstructive pulmonary disease and type 2 diabetes.
Postgraduate medical journal
May 18, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) are on the rise. While there is evidence of a link between the two diseases, the pathophysiological mechanisms they share are not fully understood.
scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework.
Cell genomics
May 14, 2025
Transcriptome-wide association studies (TWASs) help identify disease-causing genes but often fail to pinpoint disease mechanisms at the cellular level because of the limited sample sizes and sparsity of cell-type-specific expression data. Here, we pr...
Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus.
Scientific reports
May 12, 2025
Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to deve...
The Effectiveness of a Custom AI Chatbot for Type 2 Diabetes Mellitus Health Literacy: Development and Evaluation Study.
Journal of medical Internet research
May 5, 2025
BACKGROUND: People living with chronic diseases are increasingly seeking health information online. For individuals with diabetes, traditional educational materials often lack reliability and fail to engage or empower them effectively. Innovative app...
Investigating the Link between Type 2 Diabetes and Epstein-Barr Virus: a Machine Learning and Mendelian Randomization.
Clinical laboratory
May 1, 2025
BACKGROUND: Epstein-Barr virus (EBV) is a ubiquitous herpesvirus that is known to cause infectious mononucleosis and is associated with several autoimmune diseases and cancers through immune system dysregulation and chronic inflammatory mechanisms.
Real-Time AI-Assisted Insulin Titration System for Glucose Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial.
JAMA network open
May 1, 2025
IMPORTANCE: Type 2 diabetes (T2D) is one of the most prevalent chronic diseases in the world. Insulin titration for glycemic control in T2D is crucial but limited by the lack of personalized and real-time tools.
Integrating Artificial Intelligence in the Diagnosis and Management of Metabolic Syndrome: A Comprehensive Review.
Diabetes/metabolism research and reviews
May 1, 2025
BACKGROUND: Metabolic syndrome (MetS) is a progressive chronic pathophysiological state characterised by abdominal obesity, hypertension, hyperglycaemia, and dyslipidaemia. It is recognised as one of the major clinical syndromes affecting human healt...
Prediction of Hypoglycemia From Continuous Glucose Monitoring in Insulin-Treated Patients With Type 2 Diabetes Using Transfer Learning on Type 1 Diabetes Data: A Deep Transfer Learning Approach.
Journal of diabetes science and technology
May 1, 2025
BACKGROUND: Hypoglycemia is common in insulin-treated type 2 diabetes (T2D) patients, which can lead to decreased quality of life or premature death. Deep learning models offer promise of accurate predictions, but data scarcity poses a challenge. Thi...
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