Endocrinology

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

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Correlation Is Not Enough: Embedding Human Metadata for Individual Causal Discovery

Ask a pretrained biomedical language model whether "cortisol 28 ug/dL" and "stock-market volatility"...

MultiAge: A New Multidimensional Biomarker of Biological Age Derived from Comprehensive Phenotypic and Molecular Profiling

Background: It is an everyday observation that people of the same chronological age differ with resp...

Calibrating trust in AI-assisted pituitary surgery

Background: Endoscopic endonasal transsphenoidal surgery (EETS) requires navigation around neurocrit...

Exploring the Interpretability of AI Decision Support Systems for Surgical Anatomy Recognition

Artificial intelligence (AI) decision support systems for surgery hold promise but face barriers to ...

MealRes-Gate: Forecasting Glucose Dynamics from CGM and Sparse Meal Logs Using Residual-Gated Multimodal Transformer

Continuous glucose monitoring (CGM) enables personalized metabolic health support, but forecasting g...

Deep Longitudinal Clusters of Type 2 Diabetes Pathophysiology and their Risk of Cardiovascular Disease Events and All-Cause Mortality

Objective: Despite the complex and non-linear progression of diabetes, its shared pathways with athe...

A Deep Learning-Based Predictive Algorithm for Metabolic Syndrome Detection in the U.S. Population

Objective To develop clinically operational, population-representative risk-score models for detecti...

Neovascular Glaucoma at a Tertiary Centre in Finland, 2008-2024: A Retrospective Cohort Study

Background/Aims: Neovascular glaucoma (NVG) is an aggressive secondary glaucoma with limited longitu...

Smart AI-Powered Machine Learning Risk Assessment for Early Osteoporosis Detection for Women Bone Health

Osteoporosis is often called a silent disease because it progresses without symptoms until a fractur...

Title: Zero-shot automated insulin delivery for type 1 diabetes via dynamic physiology-aware reinforcement learning

Insulin therapy for type 1 diabetes requires continual dose adjustment to meals, activity, stress, i...

Glycemic response trajectories on metformin monotherapy in real-world diabetes care

Objectives: Diabetes affects over 500 million people globally and glycemia is inadequately managed. ...

Implementation of Big Data Analytics for Diabetes Management: Needs Assessment in the Rwanda Healthcare System

Diabetes is a chronic metabolic disease that can lead to serious health problems if not diagnosed an...

ConvNeXt-FD: A Fractal-Based Deep Model for Robust Biomedical Image Segmentation

Biomedical image segmentation is a critical task in medical diagnosis and treatment planning, enabli...

Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes

Diabetes is a global health burden, and early detection is critical for timely intervention. This st...

Decoding heterogeneous aging clocks and disease risk stratification using a metabolomic foundation model

Metabolomic aging clocks estimate biological age by modeling metabolite concentrations, thereby capt...

Interpretable Predictive Modeling for Medical Data Using Boolean Rule-aware Regression

Purpose: In clinical practice, accurate prediction of disease risk must be accompanied by transparen...

Elevated serum apolipoprotein B and lipoprotein remodelling distinguish adults with HLH from HLH mimics and controls

Haemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening hyperinflammatory syndrome cha...

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