Diabetes

Deep-Learning-Based Blood Glucose Detection Device Using Acetone Exhaled Breath Sensing Features of α-FeO-MWCNT Nanocomposites.

Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the devel...

Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.

BACKGROUND: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipos...

Ethical Considerations in the Design and Conduct of Clinical Trials of Artificial Intelligence.

IMPORTANCE: Safe integration of artificial intelligence (AI) into clinical settings often requires r...

SCINet: A Segmentation and Classification Interaction CNN Method for Arteriosclerotic Retinopathy Grading.

As a common disease, cardiovascular and cerebrovascular diseases pose a great harm threat to human w...

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning (Diabetes Metab J 2024;48:771-9).

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning (Diabetes Metab J 2024;48:771-9).

The early prediction of gestational diabetes mellitus by machine learning models.

BACKGROUND: We aimed to determine the best-performing machine learning (ML)-based algorithm for pred...

Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning.

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristic...

Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical prese...

Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominen...

Development of oculomics artificial intelligence for cardiovascular risk factors: A case study in fundus oculomics for HbA1c assessment and clinically relevant considerations for clinicians.

Artificial Intelligence (AI) is transforming healthcare, notably in ophthalmology, where its ability...

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study a...

Machine learning assessment of vildagliptin and linagliptin effectiveness in type 2 diabetes: Predictors of glycemic control.

OBJECTIVE: Differential effects of linagliptin and vildagliptin may help us personalize treatment fo...

Metadata information and fundus image fusion neural network for hyperuricemia classification in diabetes.

OBJECTIVE: In diabetes mellitus patients, hyperuricemia may lead to the development of diabetic comp...

The use of artificial neural networks in studying the progression of glaucoma.

In ophthalmology, artificial intelligence methods show great promise due to their potential to enhan...

Risk factors for the time to development of retinopathy of prematurity in premature infants in Iran: a machine learning approach.

BACKGROUND: Retinopathy of prematurity (ROP), is a preventable leading cause of blindness in infants...

Interpretable machine learning models based on shear-wave elastography radiomics for predicting cardiovascular disease in diabetic kidney disease patients.

BACKGROUND: The risk of cardiovascular complications is significantly elevated in patients with diab...

Machine learning-based reproducible prediction of type 2 diabetes subtypes.

AIMS/HYPOTHESIS: Clustering-based subclassification of type 2 diabetes, which reflects pathophysiolo...

Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: A pediatric population-based longitudinal study.

Pediatric obesity can drastically heighten the risk of cardiometabolic alterations later in life, wi...

A novel approach for automatic classification of macular degeneration OCT images.

Age-related macular degeneration (AMD) and diabetic macular edema (DME) are significant causes of bl...

Impact of Gold-Standard Label Errors on Evaluating Performance of Deep Learning Models in Diabetic Retinopathy Screening: Nationwide Real-World Validation Study.

BACKGROUND: For medical artificial intelligence (AI) training and validation, human expert labels ar...