Diabetes

Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data.

BACKGROUND: In recent years, numerous methods have been introduced to predict glucose levels using m...

Identification of Key Efferocytosis-Related Genes and Mechanisms in Diabetic Retinopathy.

This study aimed to explore the key efferocytosis-related genes in diabetic retinopathy (DR) and the...

Hybrid deep learning models for the screening of Diabetic Macular Edema in optical coherence tomography volumes.

Several studies published so far used highly selective image datasets from unclear sources to train ...

Predicting recurrent gestational diabetes mellitus using artificial intelligence models: a retrospective cohort study.

BACKGROUND: We aimed to develop novel artificial intelligence (AI) models based on early pregnancy f...

Evaluation of an AI algorithm trained on an ethnically diverse dataset to screen a previously unseen population for diabetic retinopathy.

PURPOSE: This study aimed to determine the generalizability of an artificial intelligence (AI) algor...

RACGAP1 is a pivotal gene in lung adenocarcinoma-associated membranous nephropathy: Based on comprehensive bioinformatics analysis and machine learning.

BACKGROUND: This study performs a detailed bioinformatics and machine learning analysis to investiga...

The transformative role of artificial intelligence in diabetes care and research.

Artificial intelligence chatbots for the nutrition management of diabetes and the metabolic syndrome.

BACKGROUND: Recently, there has been a growing interest in exploring AI-driven chatbots, such as Cha...

The role of saliency maps in enhancing ophthalmologists' trust in artificial intelligence models.

PURPOSE: Saliency maps (SM) allow clinicians to better understand the opaque decision-making process...

A deep learning framework for the early detection of multi-retinal diseases.

Retinal images play a pivotal contribution to the diagnosis of various ocular conditions by ophthalm...

Proposing a New Frontier in Diabetes Treatment: The Integration of Biotechnology and Artificial Intelligence.

Computational approaches for clinical, genomic and proteomic markers of response to glucagon-like peptide-1 therapy in type-2 diabetes mellitus: An exploratory analysis with machine learning algorithms.

INTRODUCTION: In 2021, the International Diabetes Federation reported that 537 million people worldw...

Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors.

BACKGROUND: Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are sig...

Integrated image-based deep learning and language models for primary diabetes care.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challen...

A deep learning approach to hard exudates detection and disorganization of retinal inner layers identification on OCT images.

The purpose of the study was to detect Hard Exudates (HE) and classify Disorganization of Retinal In...

[OCT biomarkers in diabetic maculopathy and artificial intelligence].

Diabetes mellitus is a chronic disease the microvascular complications of which include diabetic ret...

A transparent machine learning algorithm uncovers HbA1c patterns associated with therapeutic inertia in patients with type 2 diabetes and failure of metformin monotherapy.

AIMS: This study aimed to identify and categorize the determinants influencing the intensification o...

Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.

BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clini...

Machine learning-based prediction of diabetic patients using blood routine data.

Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for...

Development and validation of 10-year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning-based methods.

AIM: To develop 10-year cardiovascular disease (CVD) risk prediction models in Chinese patients with...

Enhancing Diabetes Management for Older Patients: The Potential Role of ChatGPT.

Artificial intelligence (AI) technology has the potential to improve diabetes education for older in...