AIMC Topic: Diabetes Mellitus
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A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases.
Journal of biomedical informatics
Aug 1, 2015
Automated phenotype identification plays a critical role in cohort selection and bioinformatics data mining. Natural Language Processing (NLP)-informed classification techniques can robustly identify phenotypes in unstructured medical notes. In this ...
Phenotype
Electronic Health Records
Obesity
Humans
Natural Language Processing
Data Mining
Diagnosis, Computer-Assisted
New York
Decision Support Systems, Clinical
Pattern Recognition, Automated
Diabetes Mellitus
Reproducibility of Results
Support Vector Machine
Sensitivity and Specificity
Cardiovascular Diseases
Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes.
IEEE journal of biomedical and health informatics
May 19, 2014
Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown that 50-80% proportion of T2DM is undiagnosed. In this paper, support vector machines are utilized to screen diabetes, and an ensemble learning module i...
Creating a place for caregivers in personal health: the iHealthSpace copilot program and diabetes care.
Journal of diabetes science and technology
Jan 1, 2011
BACKGROUND: As America's baby boom generation reaches retirement, the number of elders, and, in turn, the number of lay individuals who support them, will continue to increase. With the important services caregivers provide, it is critical that we re...
A scoping review of digital solutions in diabetes outpatient care: Functionalities and outcomes.
International journal of medical informatics
Oct 1, 2025
BACKGROUND: Digital interventions are increasingly used in outpatient diabetes care to address growing healthcare demands and workforce limitations. This study investigates the functionalities of digital solutions and their impact on Quadruple Aim ou...
ICU Length of Stay Prediction for Patients with Diabetes Using Machine Learning and Clinical Notes.
Studies in health technology and informatics
Aug 7, 2025
Diabetes, a chronic disease, often leads to poor health outcomes and increased healthcare costs, particularly for patients admitted to ICU. Accurate early prediction of ICU length of stay (LOS) is vital for hospital resource management and patient ou...
Enhancing Chronic Diabetes Care with Companion Robots in Rural Taiwan.
Studies in health technology and informatics
Aug 7, 2025
Managing chronic diabetes in rural Taiwan remains challenging due to limited medical access and low health literacy. This pilot study evaluated a two-month, two-phase intervention using Bluetooth-enabled glucometers, smart wristbands, and a gamified ...
Predicting Diabetes Using Convolutional Neural Networks and EKG Entropy Analysis.
Studies in health technology and informatics
Aug 7, 2025
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
Aug 1, 2025
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
Jul 1, 2025
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
Jul 1, 2025
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...
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