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Diabetes Mellitus

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Development of Various Diabetes Prediction Models Using Machine Learning Techniques.

Diabetes & metabolism journal
BACKGROUND: There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters.

Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy.

Journal of diabetes research
AIMS: To investigate the applicability of deep learning image assessment software VeriSee DR to different color fundus cameras for the screening of diabetic retinopathy (DR).

Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study.

The Lancet. Digital health
BACKGROUND: Diabetic retinopathy is a leading cause of preventable blindness, especially in low-income and middle-income countries (LMICs). Deep-learning systems have the potential to enhance diabetic retinopathy screenings in these settings, yet pro...

Deep Learning Algorithm-Based MRI Image in the Diagnosis of Diabetic Macular Edema.

Contrast media & molecular imaging
This study investigates the value of magnetic resonance imaging (MRI) based on a deep learning algorithm in the diagnosis of diabetic macular edema (DME) patients. A total of 96 patients with DME were randomly divided into the experimental group (  =...

Untangling Computer-Aided Diagnostic System for Screening Diabetic Retinopathy Based on Deep Learning Techniques.

Sensors (Basel, Switzerland)
Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss. Approximately 285 million worldwide population is affected with diabetes, and one-third of these patients have symptoms of DR. Specifically, it tends to affect the patien...

A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, the long-term complications often remain undetected at the early stages of diagnosis. Developing a ma...

A Novel Extra Tree Ensemble Optimized DL Framework (ETEODL) for Early Detection of Diabetes.

Frontiers in public health
Diabetes has been recognized as a global medical problem for more than half a century. Patients with diabetes can benefit from the Internet of Things (IoT) devices such as continuous glucose monitoring (CGM), intelligent pens, and similar devices. Sm...

A machine learning-based on-demand sweat glucose reporting platform.

Scientific reports
Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause of morbidity, resulting in a reduced quality of life even in developed societies, primarily affected...

Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods.

BMC medical informatics and decision making
BACKGROUND: Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate predict...

The adoption of deep learning interpretability techniques on diabetic retinopathy analysis: a review.

Medical & biological engineering & computing
Diabetic retinopathy (DR) is a chronic eye condition that is rapidly growing due to the prevalence of diabetes. There are challenges such as the dearth of ophthalmologists, healthcare resources, and facilities that are unable to provide patients with...