Endocrinology

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

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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...

Thy-DAMP: deep artificial neural network model for prediction of thyroid cancer mortality.

PURPOSE: Despite the rising incidence of differentiated thyroid cancer (DTC), mortality rates have r...

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

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

A prognostic model for thermal ablation of benign thyroid nodules based on interpretable machine learning.

INTRODUCTION: The detection rate of benign thyroid nodules is increasing every year, with some affec...

F-Net: Follicles Net an efficient tool for the diagnosis of polycystic ovarian syndrome using deep learning techniques.

The study's primary objectives encompass the following: (i) To implement the object detection of ova...

Optimization of diabetes prediction methods based on combinatorial balancing algorithm.

BACKGROUND: Diabetes, as a significant disease affecting public health, requires early detection for...

Decoding the NCCN Guidelines With AI: A Comparative Evaluation of ChatGPT-4.0 and Llama 2 in the Management of Thyroid Carcinoma.

INTRODUCTION: Artificial Intelligence (AI) has emerged as a promising tool in the delivery of health...

Insertable Glucose Sensor Using a Compact and Cost-Effective Phosphorescence Lifetime Imager and Machine Learning.

Optical continuous glucose monitoring (CGM) systems are emerging for personalized glucose management...

Real-world evaluation of RetCAD deep-learning system for the detection of referable diabetic retinopathy and age-related macular degeneration.

CLINICAL RELEVANCE: The challenges of establishing retinal screening programs in rural settings may ...

From bytes to nephrons: AI's journey in diabetic kidney disease.

Diabetic kidney disease (DKD) is a significant complication of type 2 diabetes, posing a global heal...

Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms.

: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical ...

Predictability of varicocele repair success: preliminary results of a machine learning-based approach.

Varicocele is a prevalent condition in the infertile male population. However, to date, which patien...

Learning control-ready forecasters for Blood Glucose Management.

Type 1 diabetes (T1D) presents a significant health challenge, requiring patients to actively manage...

Reinforced Computer-Aided Framework for Diagnosing Thyroid Cancer.

Thyroid cancer is the most pervasive disease in the endocrine system and is getting extensive attent...

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