Endocrinology

Predicting type II diabetes mellitus in young and middle-aged adults: A machine learning approach using the Utah population database.

AIMS: To develop a machine learning framework for predicting type 2 diabetes mellitus (T2DM) using administrative data and electronic health records (EHR) that could be applied in healthcare settings. METHODS: Study population included parents of individuals born in 1970-1990 who resided in Utah urban counties during 1990-2015. Two prediction models were developed using classification and regressi...

Indicators for predicting continuous insulin infusion therapy-related hypokalemia: multicenter retrospective cohort study.

Hypokalemia is a common and potentially life-threatening complication of continuous intravenous insulin infusion (CII) in patients with hyperglycemic crises. However, no simple quantitative indicator can estimate the risk of hypokalemia at treatment initiation. This multicenter retrospective cohort study enrolled patients hospitalized for hyperglycemic crises who received CII. Clinical data availa...

Single-cell and spatial analyses identify a glycolysis-high state driven by STOML2 in epithelial ovarian cancer.

OBJECTIVE: Metabolic heterogeneity contributes to therapeutic resistance and poor prognosis in epithelial ovarian cancer (EOC), yet the regulatory dri...

Machine learning in diagnostic stewardship: A technical approach in improving diagnostic accuracy, optimizing antibiotic use in false positive CSF cultures.

Diagnostic stewardship emphasises ordering the right tests, at the right time for the patient and also promotes the judicious use of rapid and accurat...

Remission, Relapse, and Thyroid-Related Parameters Measurement at Discontinuation of Low-Dose Anti-Thyroid Drugs in Graves' Disease.

BACKGROUND: This study aimed to elucidate the relationship between thyroid-related parameters and the prognosis of Graves' disease (GD). METHODS: This...

Obesity, microRNA circulating microRNA signatures reveal core and reversible dysregulations in obesity via machine learning.

Obesity is a complex metabolic disease characterized by systemic metabolic and inflammatory dysregulation, yet the molecular signatures underlying the...

Complication Risk Classification in Children and Adolescents With Type 1 Diabetes: Interpretable Machine Learning Study Based on Saudi Clinical Guidelines.

BACKGROUND: Complication risks in children and adolescents with type 1 diabetes (T1D) can lead to serious health outcomes if not detected early. Despi...

Clinical setting-dependent diagnostic accuracy of artificial intelligence and store-and-forward diabetic retinopathy screening: a systematic review and meta-analysis.

Population-based diabetic retinopathy (DR) screening requires diagnostic strategies that optimize clinical utility by balancing missed disease against...

Development and validation of an explainable machine learning model using routine laboratory biomarkers for identifying prevalent MASLD: Evidence from two observational studies.

Although many predictive models for metabolic dysfunction-associated steatotic liver disease (MASLD) have been developed, their performance remains su...

Interfacial impedance engineering in ionic hydrogels for integrated enzymatic and electrophysiological sensing.

Interfacial charge-transfer resistance remains a critical bottleneck in wearable enzymatic biosensors, particularly in soft, deformable systems, where...

Identification and validation of lactylation-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning.

BACKGROUND: The pathogenic mechanisms underlying rheumatoid arthritis (RA) remain elusive. Lactylation, a novel post-translational modification, may r...

Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study.

OBJECTIVE: To explore clinically meaningful phenotypes of preeclampsia using unsupervised machine learning. DESIGN: Prospective cohort study. SETTING:...

Machine learning-driven identification of circulating biomarkers and therapeutic compounds for diabetic retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a major cause of severe visual impairment, where early diagnosis and intervention are crucial to prevent irre...

Transcriptomic sequencing analysis of the tumor microenvironment atlas and potential mechanisms of metastasis in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is the most prevalent thyroid malignancy and its incidence continues to rise. Although prognosis is generally favora...

AI-powered and manual assessment of tumor-infiltrating lymphocytes in early HER2-positive breast cancer in NSABP B-41.

The assessment of tumor-infiltrating lymphocyte (TILs), together with gene expression signatures (GES), has the potential to guide personalized breast...

Digital twin- enabled intelligent HMI for real-time industrial automation systems.

The research is devoted to solving the urgent problem of industrial production intellectualization based on the creation of an intelligent HMI display...

EXPRESS: Artificial Intelligence in Diabetes Care: Toward Precision Diagnosis and Personalized Management.

AimsDiabetes mellitus is a global health challenge requiring innovative solutions for early diagnosis, personalized treatment, and ongoing management....

Adrenal gland dysfunction in males with cluster headache.

BACKGROUND: Cluster headache is associated with compensated hypogonadism in males, suggesting impaired testicular steroidogenesis. It is unknown if ad...

Non-traditional metabolic indices predict incident circadian syndrome in middle-aged and older Chinese adults: a nationwide prospective cohort study and machine learning analysis.

BACKGROUND: Circadian syndrome (CircS) augments the conventional metabolic syndrome construct by adding disturbed sleep and depressive features. Wheth...

Underperformance of Machine Learning Algorithms Predicting Extended Lengths of Stay and Readmission in Underrepresented Patient Cohorts After Primary Total Hip Arthroplasty.

BACKGROUND: The demand for total hip arthroplasty (THA) is increasing, yet disparities in access and outcomes persist across racial, ethnic, and socio...