AIMC Topic: Diabetes Complications

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Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.

Asia-Pacific journal of public health Apr 18, 2025
This study aimed to develop machine learning (ML) models to predict diabetic complications in patients with type 2 diabetes (T2D) in Malaysia. Data from the Malaysian National Diabetes Registry and Death Register were used to develop predictive model...
Humans Machine Learning Diabetes Mellitus, Type 2 Malaysia Registries Female Diabetes Complications Aged Male Middle Aged
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Predicting diabetes mellitus metabolic goals and chronic complications transitions-analysis based on natural language processing and machine learning models.

PloS one Apr 15, 2025
OBJECTIVE: To estimate Diabetes mellitus (DM) progression at one and two years in terms of glycemic targets and development of complications.
Glycated Hemoglobin Diabetes Complications Disease Progression Blood Glucose Diabetes Mellitus Natural Language Processing Machine Learning Retrospective Studies Electronic Health Records Female Aged Humans Adult Male Middle Aged
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Diabetes and Cataracts Development-Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study.

Medicina (Kaunas, Lithuania) Dec 28, 2024
Diabetes has become a global epidemic, contributing to significant health challenges due to its complications. Among these, diabetes can affect sight through various mechanisms, emphasizing the importance of early identification and management of vi...
Machine Learning Female Aged Adult Humans Cataract Cross-Sectional Studies Diabetes Complications Male Romania Middle Aged Diabetes Mellitus
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Artificial Intelligence to Diagnose Complications of Diabetes.

Journal of diabetes science and technology Nov 22, 2024
Artificial intelligence (AI) is increasingly being used to diagnose complications of diabetes. Artificial intelligence is technology that enables computers and machines to simulate human intelligence and solve complicated problems. In this article, w...
Humans Artificial Intelligence Diabetes Complications
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Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand.

BMC medical informatics and decision making Sep 27, 2024
BACKGROUND: In the age of big data, linked social and administrative health data in combination with machine learning (ML) is being increasingly used to improve prediction in chronic disease, e.g., cardiovascular diseases (CVD). In this study we aime...
Aged Ethnicity Adult Health Status Disparities Male Diabetes Complications Middle Aged Humans Cardiovascular Diseases Risk Assessment Machine Learning Diabetes Mellitus Female New Zealand
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Enhancing pharmacist intervention targeting based on patient clustering with unsupervised machine learning.

Expert review of pharmacoeconomics & outcomes research Sep 23, 2024
OBJECTIVES: Adherence to the American Diabetes Association (ADA) Standards of Medical Care is low. This study aimed to assist pharmacists in identifying patients for diabetes control interventions using unsupervised machine learning.
Diabetes Complications Pharmacists Professional Role Pharmaceutical Services Unsupervised Machine Learning Insurance, Health Self Report Sex Factors Male Middle Aged Surveys and Questionnaires Machine Learning United States Female Hypoglycemic Agents Aged Diabetes Mellitus Adult Age Factors Humans Cluster Analysis
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Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model.

Journal of diabetes and its complications Oct 3, 2022
Management of diabetes requires a multifaceted approach of risk factor reduction; through management of risk factors such as glucose, blood pressure and cholesterol. Goals for these risk factors often vary and guidelines suggest that this is based on...
Humans Diabetes Complications Artificial Intelligence Machine Learning Risk Factors Clinical Trials as Topic
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A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.

IEEE journal of biomedical and health informatics Sep 3, 2021
People with diabetes require lifelong access to healthcare services to delay the onset of complications. Their disease management processes generate great volumes of data across several domains, from clinical to administrative. Difficulties in access...
Risk Factors Cardiovascular Diseases Deep Learning Diabetes Mellitus Stroke Myocardial Infarction Diabetes Complications Humans
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Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.

BMC endocrine disorders May 4, 2021
INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and v...
Survival Analysis Hong Kong Diabetes Complications Blood Glucose Diabetes Mellitus Humans Lipids Machine Learning Glycated Hemoglobin Computer Simulation Aged Prognosis Adult Retrospective Studies Male Female Middle Aged Risk Factors
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Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports.

PloS one Aug 19, 2020
STUDY AIM: To develop and apply a natural language processing algorithm for characterization of patients diagnosed with chronic pancreatitis in a diverse integrated U.S. healthcare system.
Pancreatitis, Chronic Smoking Proportional Hazards Models Kaplan-Meier Estimate Diabetes Complications Sensitivity and Specificity Male Middle Aged Female Body Mass Index Image Processing, Computer-Assisted Humans Risk Factors Retrospective Studies Pancreatic Neoplasms Aged Tomography, X-Ray Computed Natural Language Processing Adult Pancreas
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