AIMC Topic: Diabetes Mellitus
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Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.
European journal of ophthalmology
Apr 27, 2022
PURPOSE: Artificial intelligence (AI) can detect diabetic macular edema (DME) from optical coherence tomography (OCT) images. We aimed to evaluate the performance of deep learning neural networks in DME detection.
A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.
Computational intelligence and neuroscience
Apr 15, 2022
An active research area where the experts from the medical field are trying to envisage the problem with more accuracy is diabetes prediction. Surveys conducted by WHO have shown a remarkable increase in the diabetic patients. Diabetes generally rema...
Robot-enhanced diabetes care for middle-aged and older adults living with diabetes in the community: A small sample size mixed-method evaluation.
PloS one
Apr 15, 2022
PURPOSE: This study assessed robot-enhanced healthcare in practical settings for the purpose of community diabetes care.
Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.
JMIR mHealth and uHealth
Apr 4, 2022
BACKGROUND: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development o...
Development of Various Diabetes Prediction Models Using Machine Learning Techniques.
Diabetes & metabolism journal
Mar 11, 2022
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
Mar 9, 2022
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
Mar 7, 2022
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
Mar 4, 2022
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)
Feb 24, 2022
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
Feb 21, 2022
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...
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