Endocrinology

Stress hyperglycemia ratio and mortality risk in cardiometabolic multimorbidity: a multicenter retrospective study.

Predicting progression-free survival in hormone-receptor positive (HR+/HER2-) metastatic breast cancer (MBC) treated with CDK4/6 inhibitors: A machine learning approach.

BACKGROUND: In HR+/HER2- metastatic breast cancer (MBC), CDK4/6 inhibitors combined with endocrine t...

Characterizing the Immune Cell Infiltration in Renal Interstitium and Therapeutic Targets of Drugs in Diabetic Nephropathy by Multiomics Study.

BACKGROUND: Immune cell infiltration in the renal interstitium contributes to the progression of dia...

Mechanism Based Hierarchical Machine Learning for High-Throughput Quantitative Prediction of Estrogenic, Androgenic, and Thyroid Disruption Activities.

Although qualitative predictions of endocrine-disrupting chemicals (EDCs) are well established, quan...

Childhood dyslexia risk elevated by heavy metal mixtures from e-waste: A machine learning-driven mixture modeling study.

Environmental heavy metal mixtures from informal e-waste recycling are potential neurotoxicants, but...

A CT-based radiomics model for classification of chronic pancreatitis: new biomarkers for diagnosis and severity staging.

OBJECTIVES: To develop and validate CT-based radiomics models for the identification of chronic panc...

Novel mechanisms of atrazine endocrine disruption: an integrated approach reveals progesterone and glucocorticoid receptor targeting.

Integrated omics and machine learning uncover the molecular basis of environmental toxicant 6PPD-Qinduced non-obstructive azoospermia.

BACKGROUND: N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q), a transformation pr...

Double Graph Attention Network for predicting non-alcoholic fatty liver disease in patients with type 2 diabetes.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, while non-alcoholic fatty liver dise...

Explainable reinforcement learning for glucose monitoring based on shapley value analysis.

BACKGROUND AND OBJECTIVE: Effective diabetes management requires continuous regulation of blood gluc...

Automated deep learning for detection and measurement of adrenal masses in contrast-enhanced abdominal CT.

OBJECTIVES: Adrenal tumors can be functional or malignant, yet they are often overlooked in abdomina...

Characterization of Models for Identifying Physical and Cognitive Frailty in Older Adults With Diabetes: Systematic Review and Meta-Analysis.

BACKGROUND: Physical frailty and cognitive frailty are increasingly recognized as critical geriatric...

Optimizing Early Detection of Diabetic Kidney Disease through Synergistic Biomarkers and Serum Metabolites in Human.

BACKGROUND: Diabetic kidney disease (DKD) progresses to end-stage renal disease more rapidly than ch...

Development of a machine learning-based model for prediction of diabetes risk in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading chronic li...

Hierarchical image pyramid transformer framework for automated breast cancer molecular subtyping using tissue microarrays.

The heterogeneity of breast cancer at molecular and histological levels poses significant challenges...

Immune system up-regulation in securely attached infants during early childhood.

Early caregiving relationships shape the coordination of stress and immune systems, yet their biolog...

Key evidence for personalised nutrition: a review of randomised controlled trials.

The field of personalised nutrition is growing and is based on the concept that delivering personali...

Deciphering Multitarget Mechanisms of Phytochemical Flavonoids From Traditional Chinese Medicine: Emerging Insights Into Osteoporosis Therapeutics.

Osteoporosis is a common metabolic bone disorder characterized by reduced bone mass and compromised ...

Interpretable machine learning model for predicting refeeding syndrome after colorectal cancer surgery.

OBJECTIVE: Refeeding syndrome (RFS) is a common yet frequently overlooked complication during postop...

Bioinspired Multifunctional Hydrogels for Deep Learning-Enabled Wound pH Visual Monitoring and Treatment.

Smart wound dressings capable of real-time environmental monitoring and therapeutic intervention are...

Machine learning-based models for preoperative prediction of pituitary adenoma consistency: a systematic review and meta-analysis.

BACKGROUND/OBJECTIVES: The consistency of pituitary adenoma (PA) significantly impacts surgical diff...