AIMC Topic: Diabetes Mellitus

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Predicting Diabetes Using Convolutional Neural Networks and EKG Entropy Analysis.

Studies in health technology and informatics
Heart Rate Variability (HRV) is associated with diabetic complications. This analysis can quantify changes in heart rate variability, and it may help detect early alterations in diabetes. This study aimed to design and validate a Convolutional Neural...

Effectiveness of AI-driven interventions in glycemic control: A systematic review and meta-analysis of randomized controlled trials.

Primary care diabetes
This systematic review aims to assess the effectiveness of AI-Driven Decision Support Systems in improving glycemic control, measured by Time in Range (TIR) and HbA1c levels, in patients with diabetes. Included studies were randomized controlled tria...

Recommendations for the Management of Diabetes During Ramadan Applying the Principles of the ADA/ EASD Consensus: Update 2025.

Diabetes/metabolism research and reviews
Ramadan fasting is a sacred ritual observed by approximately 1.8 billion Muslims each year, most of whom adhere to fasting due to its significance as a core pillar of Islam. Able-bodied Muslims who are capable of fasting are religiously required to d...

Development and validation of a convenient dementia risk prediction tool for diabetic population: A large and longitudinal machine learning cohort study.

Journal of affective disorders
BACKGROUND: Diabetes mellitus has been shown to increase the risk of dementia, with diabetic patients demonstrating twice the dementia incidence rate of non-diabetic populations. We aimed to develop and validate a novel machine learning-based dementi...

A dynamic model using k-NN algorithm for predicting diabetes and breast cancer.

Computers in biology and medicine
Healthcare remains a critical focus due to its direct impact on human well-being. Diabetes, currently the fastest-growing chronic disease globally, poses severe health risks, including cardiovascular complications and kidney failure. Simultaneously, ...

Recent trends in diabetes mellitus diagnosis: an in-depth review of artificial intelligence-based techniques.

Diabetes research and clinical practice
Diabetes mellitus (DM) is a highly prevalent chronic condition with significant health and economic impacts; therefore, an accurate diagnosis is essential for the effective management and prevention of its complications. This review explores the late...

Advances in artificial intelligence for diabetes prediction: insights from a systematic literature review.

Artificial intelligence in medicine
Diabetes mellitus (DM), a prevalent metabolic disorder, has significant global health implications. The advent of machine learning (ML) has revolutionized the ability to predict and manage diabetes early, offering new avenues to mitigate its impact. ...

Integrating large language models with human expertise for disease detection in electronic health records.

Computers in biology and medicine
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...

SNER: Semi-Supervised Named Entity Recognition for Large Volume of Diabetes Data.

IEEE journal of biomedical and health informatics
The medical literature and records on diabetes provide crucial resources for diabetes prevention and treatment. However, extracting entities from these textual diabetes data is crucial but challenging. Named entity recognition (NER) - an important co...