Endocrinology

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

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Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.

This study aimed to develop a machine learning (ML) model for predicting the risk of acute kidney in...

Hybrid deep learning framework for diabetic retinopathy classification with optimized attention AlexNet.

Diabetic retinopathy (DR) is a chronic condition associated with diabetes that can lead to vision im...

Toward Accurate Deep Learning-Based Prediction of Ki67, ER, PR, and HER2 Status From H&E-Stained Breast Cancer Images.

Despite improvements in machine learning algorithms applied to digital pathology, only moderate accu...

Future horizons in diabetes: integrating AI and personalized care.

Diabetes is a global health crisis with rising incidence, mortality, and economic burden. Traditiona...

Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.

PURPOSE: We aimed to identify the mitochondria-related feature genes associated with type 2 diabetes...

Interpretable machine learning-based insights into early-life endocrine disruptor exposure and small vulnerable newborns.

Early-life exposure to endocrine-disrupting chemicals (EDCs) may contribute to small vulnerable newb...

Interpretable machine learning method to predict the risk of pre-diabetes using a national-wide cross-sectional data: evidence from CHNS.

OBJECTIVE: The incidence of Type 2 Diabetes Mellitus (T2DM) continues to rise steadily, significantl...

Thyroid nodule classification in ultrasound imaging using deep transfer learning.

BACKGROUND: The accurate diagnosis of thyroid nodules represents a critical and frequently encounter...

An interpreting machine learning models to predict amputation risk in patients with diabetic foot ulcers: a multi-center study.

BACKGROUND: Diabetic foot ulcers (DFUs) constitute a significant complication among individuals with...

Brain tumor intelligent diagnosis based on Auto-Encoder and U-Net feature extraction.

Preoperative classification of brain tumors is critical to developing personalized treatment plans, ...

Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea.

To prevent chronic disease from getting worse, it is important to detect and predict it at an early ...

Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007-2018.

OBJECTIVES: This study aimed to compare the performance of five machine learning algorithms to predi...

Machine learning-based risk prediction model for neuropathic foot ulcers in patients with diabetic peripheral neuropathy.

BACKGROUND: Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes, marke...

Personalized Blood Glucose Forecasting From Limited CGM Data Using Incrementally Retrained LSTM.

For people with Type 1 diabetes (T1D), accurate blood glucose (BG) forecasting is crucial for the ef...

A diagnostic model for polycystic ovary syndrome based on machine learning.

Diagnosis of polycystic ovary syndrome remains a challenge. In this study, we propose constructing a...

The relationship between epigenetic biomarkers and the risk of diabetes and cancer: a machine learning modeling approach.

INTRODUCTION: Epigenetic biomarkers are molecular indicators of epigenetic changes, and some studies...

Can Artificial Intelligence Software be Utilised for Thyroid Multi-Disciplinary Team Outcomes?

OBJECTIVES: ChatGPT is one of the most publicly available artificial intelligence (AI) softwares. Ea...

Machine Learning-Assisted Portable Dual-Readout Biosensor for Visual Detection of Milk Allergen.

Beta-lactoglobulin (β-LG), the primary allergen in cow's milk, makes developing a rapid, sensitive, ...

Machine learning applications to classify and monitor medication adherence in patients with type 2 diabetes in Ethiopia.

BACKGROUND: Medication adherence plays a crucial role in determining the health outcomes of patients...

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