Diabetes

Prediction model of pressure injury occurrence in diabetic patients during ICU hospitalization--XGBoost machine learning model can be interpreted based on SHAP.

BACKGROUND: The occurrence of pressure injury in patients with diabetes during ICU hospitalization c...

Identifying Main Themes in Diabetes Management Interviews Using Natural Language Processing-Based Text Mining.

This study aimed to identify the main themes from exit interviews of adult patients with type 2 diab...

A Scoping Review of Studies Using Artificial Intelligence Identifying Optimal Practice Patterns for Inpatients With Type 2 Diabetes That Lead to Positive Healthcare Outcomes.

The objective of this scoping review was to survey the literature on the use of AI/ML applications i...

Recognition of diabetic retinopathy and macular edema using deep learning.

Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associate...

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

BACKGRUOUND: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long...

Physical performance strongly predicts all-cause mortality risk in a real-world population of older diabetic patients: machine learning approach for mortality risk stratification.

BACKGROUND: Prognostic risk stratification in older adults with type 2 diabetes (T2D) is important f...

Construction and evaluation of a metabolic correlation diagnostic model for diabetes based on machine learning algorithms.

BACKGROUND: Diabetes mellitus (DM) is a prevalent chronic disease marked by significant metabolic dy...

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial...

Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy.

BACKGROUND: Glomerular lesions are the main injuries of diabetic nephropathy (DN) and are used as a ...

The role of machine learning in advancing diabetic foot: a review.

BACKGROUND: Diabetic foot complications impose a significant strain on healthcare systems worldwide,...

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Desp...

Diabetic retinopathy prediction based on vision transformer and modified capsule network.

Diabetic retinopathy is considered one of the most common diseases that can lead to blindness in the...

Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.

To assess the role of artificial intelligence (AI) based automated software for detection of Diabet...

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model.

To date, there are no widely implemented machine learning (ML) models that predict progression from...

Predicting FFAR4 agonists using structure-based machine learning approach based on molecular fingerprints.

Free Fatty Acid Receptor 4 (FFAR4), a G-protein-coupled receptor, is responsible for triggering intr...

Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.

Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that...

Using Machine Learning to Construct the Blood-Follicle Distribution Models of Various Trace Elements and Explore the Transport-Related Pathways with Multiomics Data.

Permeabilities of various trace elements (TEs) through the blood-follicle barrier (BFB) play an impo...

A new intelligent system based deep learning to detect DME and AMD in OCT images.

Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular...

Effects of tacrolimus on proteinuria in Chinese and Indian patients with idiopathic membranous nephropathy: the results of machine learning study.

PURPOSE: The present study aims to explore the effects of tacrolimus on proteinuria in patients with...

Multimodality Fusion Strategies in Eye Disease Diagnosis.

Multimodality fusion has gained significance in medical applications, particularly in diagnosing cha...

Appropriateness of Artificial Intelligence Chatbots and Diabetic Foot Ulcer Management: Comment.