Endocrinology

Exploring the potential of XAI methods in generating clinically meaningful explanations for glycemia prediction in diabetes patients.

Predicting lithium-associated thyroid dysfunction through dimension reduction to establish a practical machine learning model: A retrospective multicenter study.

BACKGROUND: Thyroid dysfunction is a prevalent side effect among patients using lithium and links to refractory mood disorders. Existing predictive models are limited by high dimensionality; therefore, developing a simplified model that maintains performance is essential for clinical use. OBJECTIVE: This study aimed to develop a machine learning model to predict lithium-associated thyroid dysfunct...

Interpretable Graph Convolutional Networks for cardiovascular disease risk prediction in patients with Type 2 Diabetes Mellitus.

BACKGROUND: Cardiovascular disease (CVD) is the most prevalent complication of Type 2 Diabetes Mellitus (T2DM) and a leading cause of mortality in thi...

Combining High-Throughput Screening and In Silico Modeling to Derisk Novel Agrochemicals for Androgen Receptor Binding.

Androgen receptor (AR) modulation is a critical safety concern for environmental chemicals, including agrochemicals, due to its role in endocrine disr...

Systematic review of Artificial Intelligence-based methods for glycemic control and risk prediction in intensive care units.

BACKGROUND: Achieving safe glycemic targets in intensive care remains difficult due to rapidly changing physiology, treatment effects, and measurement...

Association of the estimated glucose disposal rate combined with a body shape index with all-cause and cardiovascular-specific mortality among individuals with cardiovascular-kidney-metabolic syndrome.

BACKGROUND: Individuals with cardiovascular-kidney-metabolic (CKM) syndrome exhibit a substantially elevated risk of all-cause and cardiovascular-spec...

Identifying serum amino acid as biomarkers of gestational diabetes mellitus in second-trimester among Chinese pregnant women: a machine learning-based cross-sectional study.

BACKGROUND: Levels of plasma branched-chain and aromatic amino acids in pregnancy have been associated with gestational diabetes mellitus (GDM), but t...

Glucose Predictions Improve Glycemic Control: A Digital Twin Evaluation.

BACKGROUND: Glucose predictions aim to empower continuous glucose monitoring (CGM) users by enabling preventive actions to reduce adverse glycemic eve...

Computational Redesign of an Ancestral Xylose Isomerase: Tuning the Substrate Preference and Thermostability for Biomass Valorization.

Xylose isomerase is a promising biocatalyst for lignocellulose valorization, but natural enzymes are limited by a preference for either d-xylose or d-...

Digital Health Solutions for Type 2 Diabetes and Prediabetes: Systematic Review of Engagement Barriers, Facilitators, and Outcomes.

BACKGROUND: Digital health interventions, including artificial intelligence (AI)-driven solutions, offer promise for type 2 diabetes mellitus (T2DM) a...

Complete Blood Count-Derived Inflammation Indices to Predict 3-Year All-Cause Mortality in Patients With Diabetes and Acute Myocardial Infarction in Critical Care: Retrospective Cohort Study With Single-Center External Validation.

BACKGROUND: Inflammation plays a pivotal role in the progression of diabetes and its cardiovascular complications, particularly acute myocardial infar...

CT Radiomics-Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study.

BACKGROUND: Thyroid carcinoma is the most prevalent endocrine malignancy, with a worldwide increasing incidence. Capsular invasion and neural invasion...

Towards the future of Endocrine Laboratory Medicine: defining the role of laboratory medicine specialists to strengthen the clinical-biological partnership - a joint opinion paper of EFLM-C:YS, IFCC TF-YS, and ESE-EYES.

Clinical endocrinology relies critically on high-quality biochemical data for diagnosis, therapeutic decisions, and long-term patient monitoring. As e...

Identification and validation of ferroptosis-related genes for diabetic nephropathy.

BACKGROUND: Emerging evidence highlights the pivotal role of ferroptosis in the pathophysiology of diabetic nephropathy (DN). This study aimed to iden...

Innovative fusion models: elevating preoperative gross ETE prediction in thyroid cancer patients.

The intratumoral and peritumoral architectural heterogeneities of papillary thyroid carcinoma (PTC) are important in preoperative prediction of gross ...

Validation of the Eyerobo FC Portable Fundus Camera for Diabetic Retinopathy Screening Using Public Datasets and Deep Learning.

INTRODUCTION: To validate the diagnostic performance of the Eyerobo FC, a new portable non-mydriatic fundus camera for diabetic retinopathy (DR) scree...

DeepStackVEGF a stacking ensemble deep learning framework for vascular endothelial growth factor prediction.

Vascular Endothelial Growth Factor (VEGF) plays a central role in angiogenesis, regulating both physiological processes such as wound healing, tissue ...

Quantitative Sensing of Monosaccharide Isomers with High Resolution and Attomolar Limit of Detection.

The quantitative detection of monosaccharide isomers holds significant promise for both the diagnosis of metabolic diseases and the development of car...

Computer-aided diagnosis of papillary thyroid carcinoma based on deep learning technology.

This article examines global thyroid cancer（TC） incidence trends, with emphasis on epidemiological patterns in China, where papillary thyroid carcinom...

Glucose forecasting and hypoglycemia forewarning in type 1 and type 2 diabetes using deep learning.

Hypoglycemia is a major barrier to safe diabetes management. Although deep learning has been widely applied to blood glucose (BG) prediction, most stu...