Diabetes

Deep learning-based hemorrhage detection for diabetic retinopathy screening.

Diabetic retinopathy is a retinal compilation that causes visual impairment. Hemorrhage is one of th...

Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.

Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal sc...

Response to: 'Deep learning synthetic angiograms for individuals unable to undergo contrast-guided laser treatment in aggressive retinopathy of prematurity'.

Implementation of five machine learning methods to predict the 52-week blood glucose level in patients with type 2 diabetes.

OBJECTIVE: For the patients who are suffering from type 2 diabetes, blood glucose level could be aff...

Nailfold capillaroscopy and deep learning in diabetes.

OBJECTIVE: To determine whether nailfold capillary images, acquired using video capillaroscopy, can ...

Prediction of ethanol fermentation under stressed conditions using yeast morphological data.

A high sugar concentration is used as a starting condition in alcoholic fermentation by budding yeas...

Identification of Glucose Transport Modulators In Vitro and Method for Their Deep Learning Neural Network Behavioral Evaluation in Glucose Transporter 1-Deficient Mice.

Metabolic flux augmentation via glucose transport activation may be desirable in glucose transporter...

Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study.

BACKGROUND: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated co...

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal pat...

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increa...

Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.

The availability of large amounts of data from continuous glucose monitoring (CGM), together with th...

Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adj...

Acute Intraoperative Hyperkalemia During Robot-Assisted Radical Cystectomy: A Case Report.

A 50-year-old man with muscle-invasive bladder cancer was scheduled for a robotic radical cystectomy...

Disease-specific data processing: An intelligent digital platform for diabetes based on model prediction and data analysis utilizing big data technology.

BACKGROUND: Artificial intelligence technology has become a mainstream trend in the development of m...

A Machine Learning Model for Prediction of Amputation in Diabetics.

BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated wi...

Quantitative measurement of blood glucose influenced by multiple factors via photoacoustic technique combined with optimized wavelet neural networks.

In this work, the photoacoustic (PA) quantitative measurement of blood glucose concentration (BGC) i...

Diabetes disease detection and classification on Indian demographic and health survey data using machine learning methods.

BACKGROUND & AIM: Diabetes mellitus has become one of the out brakes causing major health issues in ...

A regression-based machine learning approach for pH and glucose detection with redox-sensitive colorimetric paper sensors.

Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner....

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease i...

Development and validation of a machine learning-augmented algorithm for diabetes screening in community and primary care settings: A population-based study.

BACKGROUND: Opportunely screening for diabetes is crucial to reduce its related morbidity, mortality...

Deep Learning Image Analysis of Nanoplasmonic Sensors: Toward Medical Breath Monitoring.

Sensing biomarkers in exhaled breath offers a potentially portable, cost-effective, and noninvasive ...