Endocrinology

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

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Secretary bird optimization algorithm based on quantum computing and multiple strategies improvement for KELM diabetes classification.

The classification of chronic diseases has long been a prominent research focus in the field of publ...

Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study.

To explore in depth the characteristics of the risk factors for diabetes and prediabetes pathogenesi...

Paradigms of intraoperative neuromonitoring in paediatric thyroid surgery.

The larynx of children and adolescents is still in the developmental phase and the anatomical struct...

A radiopathomics model for predicting large-number cervical lymph node metastasis in clinical N0 papillary thyroid carcinoma.

OBJECTIVES: This study aimed to develop a multimodal radiopathomics model utilising preoperative ult...

Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.

This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require...

Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models.

Diabetic retinopathy, a retinal disorder resulting from diabetes mellitus, is a prominent cause of v...

A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.

Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial ...

Acute effect of endurance exercise on human milk insulin concentrations: a randomised cross-over study.

INTRODUCTION: Insulin is present in human milk and its concentration correlates with maternal circul...

Machine Learning Model for Risk Stratification of Papillary Thyroid Carcinoma Based on Radiopathomics.

RATIONALE AND OBJECTIVES: This study aims to develop a radiopathomics model based on preoperative ul...

A robust and generalized framework in diabetes classification across heterogeneous environments.

Diabetes mellitus (DM) represents a major global health challenge, affecting a diverse range of demo...

Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007-2016.

Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hyperte...

Efficient diagnosis of diabetes mellitus using an improved ensemble method.

Diabetes is a growing health concern in developing countries, causing considerable mortality rates. ...

Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction.

Diabetes, a chronic condition affecting millions worldwide, necessitates early intervention to preve...

Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning.

INTRODUCTION: Type 2 diabetes (T2D) is a complex metabolic disorder with significant global health i...

Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.

PURPOSE: Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression...

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