Endocrinology

Diabetes

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

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Comparison of 21 artificial intelligence algorithms in automated diabetic retinopathy screening using handheld fundus camera.

BACKGROUND: Diabetic retinopathy (DR) is a common complication of diabetes and may lead to irreversi...

Digital twins and artificial intelligence in metabolic disease research.

Digital twin technology is emerging as a transformative paradigm for personalized medicine in the ma...

Research on disease diagnosis based on teacher-student network and Raman spectroscopy.

Diabetic nephropathy is a serious complication of diabetes, and primary Sjögren's syndrome is a dise...

Ocular biomarkers: useful incidental findings by deep learning algorithms in fundus photographs.

BACKGROUND/OBJECTIVES: Artificial intelligence can assist with ocular image analysis for screening a...

Development and External Validation of a Multidimensional Deep Learning Model to Dynamically Predict Kidney Outcomes in IgA Nephropathy.

KEY POINTS: A dynamic model predicts IgA nephropathy prognosis based on deep learning. Longitudinal ...

Unveiling the molecular complexity of proliferative diabetic retinopathy through scRNA-seq, AlphaFold 2, and machine learning.

BACKGROUND: Proliferative diabetic retinopathy (PDR), a major cause of blindness, is characterized b...

Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.

INTRODUCTION: Metabolic syndrome (MetS) is considered to be an important parameter of cardio-metabol...

Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus.

Diabetes Mellitus is one of the oldest diseases known to humankind, dating back to ancient Egypt. Th...

Microstrip isoelectric focusing with deep learning for simultaneous screening of diabetes, anemia, and thalassemia.

BACKGROUND: Hemoglobin (Hb) is an important protein in red blood cells and a crucial diagnostic indi...

Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary ou...

SSiT: Saliency-Guided Self-Supervised Image Transformer for Diabetic Retinopathy Grading.

Self-supervised Learning (SSL) has been widely applied to learn image representations through exploi...

Pre-hospital glycemia as a biomarker for in-hospital all-cause mortality in diabetic patients - a pilot study.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with consid...

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...

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...

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...

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