Diabetes

Referable diabetic retinopathy identification from eye fundus images with weighted path for convolutional neural network.

Diabetic retinopathy (DR) is the most common cause of blindness in middle-age subjects and low DR sc...

Utilizing hybrid functional fuzzy wavelet neural networks with a teaching learning-based optimization algorithm for medical disease diagnosis.

Accurate medical disease diagnosis is considered to be an important classification problem. The main...

[Maturity Onset Diabetes of the Young: case report].

BACKGROUND: Maturity Onset Diabetes of the Young (MODY) is a type of diabetes that results from muta...

Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques.

BACKGROUND: Diabetic patients treated with intensive insulin therapies require a tight glycemic cont...

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography.

BACKGROUND AND OBJECTIVES: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric ima...

Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics.

BACKGROUND: Diabetes mellitus is a chronic disease that impacts an increasing percentage of people e...

Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs.

We have attempted to reproduce the results in Development and validation of a deep learning algorith...

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT.

Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical images. Altho...

Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive...

Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.

The lifestyle of modern society has changed significantly with the emergence of artificial intellige...

Microaneurysm detection in fundus images using a two-step convolutional neural network.

BACKGROUND AND OBJECTIVES: Diabetic retinopathy (DR) is the leading cause of blindness worldwide, an...

Instant White Rice with Pigmented Giant Embryonic Rice Improves Glucose Metabolism and Inhibits Oxidative Stress in High-Fat Diet-Fed Mice.

The effects of instant cooked rice made from a combination of white rice and pigmented giant embryon...

How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.

BACKGROUND: Self-monitoring blood glucose (SMBG) is facilitated by application available to analyze ...

Towards more Accessible Precision Medicine: Building a more Transferable Machine Learning Model to Support Prognostic Decisions for Micro- and Macrovascular Complications of Type 2 Diabetes Mellitus.

Although machine learning models are increasingly being developed for clinical decision support for ...

A pilot study of autonomous artificial intelligence-based diabetic retinopathy screening in Poland.

Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.

BACKGROUND: Radical measures are required to identify and reduce blindness due to diabetes to achiev...

Artificial intelligence for diabetic retinopathy screening in Africa.

Deep learning in ophthalmology: The technical and clinical considerations.

The advent of computer graphic processing units, improvement in mathematical models and availability...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Despite the increasing literature on the association of diabetes with inflammation, cardiovascular ...

Matched Learning for Optimizing Individualized Treatment Strategies Using Electronic Health Records.

Current guidelines for treatment decision making largely rely on data from randomized controlled tri...

Specific impact of past and new major cardiovascular events on acute kidney injury and end-stage renal disease risks in diabetes: a dynamic view.

BACKGROUND: Interconnections between major cardiovascular events (MCVEs) and renal events are recogn...