Endocrinology

Diabetes

Latest AI and machine learning research in diabetes for healthcare professionals.

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Mulberry leaves ameliorate diabetes via regulating metabolic profiling and AGEs/RAGE and p38 MAPK/NF-κB pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves have been used as traditional hypoglycemic medicine-...

Automated detection of severe diabetic retinopathy using deep learning method.

PURPOSE: The purpose of this study is to develop and validate the intelligent diagnosis of severe DR...

Machine Learning Based Diabetes Classification and Prediction for Healthcare Applications.

The remarkable advancements in biotechnology and public healthcare infrastructures have led to a mom...

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.

Identification of medical conditions using claims data is generally conducted with algorithms based ...

Hyperglycemia Identification Using ECG in Deep Learning Era.

A growing number of smart wearable biosensors are operating in the medical IoT environment and those...

Magneto-Responsive Microneedle Robots for Intestinal Macromolecule Delivery.

Oral administration is the most convenient and commonly used approach for drug delivery, while it is...

Cefepime Induced Neurotoxicity Following A Regimen Dose-Adjusted for Renal Function: Case Report and Review of the Literature.

Cefepime induced neurotoxicity (CIN) is commonly associated with renal dysfunction, however CIN can...

The Importance of Close Follow-Up in Patients with Early-Grade Diabetic Retinopathy: A Taiwan Population-Based Study Grading via Deep Learning Model.

(1) Background: Diabetic retinopathy (DR) can cause blindness. Current guidelines on diabetic eye ca...

Blood glucose concentration prediction based on VMD-KELM-AdaBoost.

The time series of blood glucose concentration in diabetic patients are time-varying, nonlinear, and...

Automated Grading of Diabetic Retinopathy with Ultra-Widefield Fluorescein Angiography and Deep Learning.

PURPOSE: The objective of this study was to establish diagnostic technology to automatically grade t...

A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.

People with diabetes require lifelong access to healthcare services to delay the onset of complicati...

EAD-Net: A Novel Lesion Segmentation Method in Diabetic Retinopathy Using Neural Networks.

Diabetic retinopathy (DR) is a common chronic fundus disease, which has four different kinds of micr...

The effect of consuming different proportions of hummer fish on biochemical and histopathological changes of hyperglycemic rats.

Hammour fish (grouper fish) are known to be of great nutritional value for human consumption, as the...

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

AIMS: This research work presented a comparative study of machine learning (ML), including two objec...

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to...

Deep Learning for Classifying Physical Activities from Accelerometer Data.

Physical inactivity increases the risk of many adverse health conditions, including the world's majo...

Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks.

Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appr...

Diagnostic performance of deep-learning-based screening methods for diabetic retinopathy in primary care-A meta-analysis.

BACKGROUND: Diabetic retinopathy (DR) affects 10-24% of patients with diabetes mellitus type 1 or 2 ...

Neovascularization Detection and Localization in Fundus Images Using Deep Learning.

Proliferative Diabetic Retinopathy (PDR) is a severe retinal disease that threatens diabetic patient...

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