Endocrinology

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

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Immunometabolic alterations in type 2 diabetes mellitus revealed by single-cell RNA sequencing: insights into subtypes and therapeutic targets.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) represents a major global health challenge, marked by ch...

Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: This systematic review aims to explore the early predictive value of machine learning (M...

Screening of obstructive sleep apnea and diabetes mellitus -related biomarkers based on integrated bioinformatics analysis and machine learning.

BACKGROUND: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still...

Exploring the triglyceride-glucose index's role in depression and cognitive dysfunction: Evidence from NHANES with machine learning support.

BACKGROUND: Depression and cognitive impairments are prevalent among older adults, with evidence sug...

DP-CLAM: A weakly supervised benign-malignant classification study based on dual-angle scanning ultrasound images of thyroid nodules.

In this paper, a two-stage task weakly supervised learning algorithm is proposed. It accurately achi...

AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus.

Pancreatic α-amylase breaks down starch into isomaltose and maltose, which are further hydrolyzed by...

A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images.

Brain tumors present a significant global health challenge, and their early detection and accurate c...

Deep learning model for automatic detection of different types of microaneurysms in diabetic retinopathy.

PURPOSE: This study aims to develop a deep-learning-based software capable of detecting and differen...

Investigating factors influencing quality of life in thyroid eye disease: insight from machine learning approaches.

AIMS: Thyroid eye disease (TED) is an autoimmune orbital disorder that diminishes the quality of lif...

A machine learning model accurately identifies glycogen storage disease Ia patients based on plasma acylcarnitine profiles.

BACKGROUND: Glycogen storage disease (GSD) Ia is an ultra-rare inherited disorder of carbohydrate me...

Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma.

This study aimed to develop and validate machine learning (ML) models to predict the occurrence of d...

Color fundus photograph-based diabetic retinopathy grading via label relaxed collaborative learning on deep features and radiomics features.

INTRODUCTION: Diabetic retinopathy (DR) has long been recognized as a common complication of diabete...

Machine learning and molecular dynamics simulations predict potential TGR5 agonists for type 2 diabetes treatment.

INTRODUCTION: Treatment of type 2 diabetes (T2D) remains a significant challenge because of its mult...

The effect of renal function on the clinical outcomes and management of patients hospitalized with hyperglycemic crises.

BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an...

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