Endocrinology

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

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Coarse for Fine: Bounding Box Supervised Thyroid Ultrasound Image Segmentation Using Spatial Arrangement and Hierarchical Prediction Consistency.

Weakly-supervised learning methods have become increasingly attractive for medical image segmentatio...

SNER: Semi-Supervised Named Entity Recognition for Large Volume of Diabetes Data.

The medical literature and records on diabetes provide crucial resources for diabetes prevention and...

MCD-LightGBM System for Intelligent Analyzing Heterogeneous Clinical Drug Therapeutic Effects.

Causal effect estimation of individual heterogeneity is a core issue in the field of causal inferenc...

Development and validation of a 3-D deep learning system for diabetic macular oedema classification on optical coherence tomography images.

OBJECTIVES: To develop and validate an automated diabetic macular oedema (DME) classification system...

Deep learning based motion correction in ultrasound microvessel imaging approach improves thyroid nodule classification.

To address inter-frame motion artifacts in ultrasound quantitative high-definition microvasculature ...

Predicting thyroid cancer recurrence using supervised CatBoost: A SHAP-based explainable AI approach.

Recurrence prediction in well-differentiated thyroid cancer remains a clinical challenge, necessitat...

NeuroScale: evolutional scale-based protein language models enable prediction of neuropeptides.

BACKGROUND: Neuropeptides (NPs) are critical signaling molecules involved in various physiological a...

Progress in the application of fludeoxyglucose positron emission tomography computed tomography in biliary tract cancer.

Biliary tract cancer (BTC) is a group of heterogeneous sporadic diseases, including intrahepatic, hi...

Machine learning based predictive model of the risk of Tourette syndrome with SHAP value interpretation: a retrospective observational study.

Tourette syndrome is a relatively prevalent neurological condition, particularly among children, cha...

Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning.

Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus. Identifying who...

A machine learning-based risk prediction model for diabetic oral ulceration.

BACKGROUND: Diabetic oral ulceration (DOU) is a prevalent and debilitating complication among diabet...

Whole-body CT-to-PET synthesis using a customized transformer-enhanced GAN.

. Positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed...

Molecular Insights into the Binding of Organophosphate Flame Retardant Key Metabolites with Mineralocorticoid and Estrogen Receptors.

Flame retardants (FR) encompass a wide range of chemicals designed to inhibit and reduce the spread ...

A circadian behavioral analysis suite for real-time classification of daily rhythms in complex behaviors.

Long-term analysis of animal behavior has been limited by reliance on real-time sensors or manual sc...

Sociodemographic Profile of People with Diagnosed Pancreatic Cancer in the UK: Retrospective Sentinel Network Cohort Study.

Pancreatic cancer is a devasting disease which is an increasing cause of cancer mortality. The aim o...

A validated multivariable machine learning model to predict cardio-kidney risk in diabetic kidney disease.

BACKGROUND: Individuals with diabetic kidney disease (DKD) often suffer cardiac and kidney events. W...

Integrating bioinformatics and machine learning to identify glomerular injury genes and predict drug targets in diabetic nephropathy.

Diabetes mellitus (DM) is a chronic metabolic disorder that poses significant challenges to public h...

Effects of neonicotinoid pesticide exposure in the first trimester on gestational diabetes mellitus based on interpretable machine learning.

BACKGROUND: Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications an...

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