Endocrinology

Hybrid deep neural network with PCA based features optimization for enhancing brain tumor classification.

Brain tumors have been an important medical concern. This is primarily due to their growth patterns have been hard to predict and their medical needs have been complicated. This work proposes emphasis on a hybrid PCA DenseNet121 convolutional neural network mechanism. The model is intended to improve classification accuracy among four specific classifications: Glioma, Meningioma, Pituitary, and No...

Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.

AIMS: The combined assessment of multiple abdominal imaging traits in relation to type 2 diabetes remains incompletely characterised. The study examines these relationships on computed tomography (CT) scans from a large-scale, racially diverse, disease-focused medical biobank. MATERIALS AND METHODS: Deep learning algorithms were applied to patients with abdominal CT scans in the Penn Medicine BioB...

A machine learning approach to predicting severe diabetes distress in adults with type 1 diabetes mellitus.

BACKGROUND: Diabetes distress is common in patients with type 1 diabetes mellitus (T1DM). The aim of this study was to construct and validate predicti...

An AI-assisted hyperbranched RCA-based colorimetric biosensing platform for ultrasensitive detection of BPA.

Bisphenol A (BPA), a common industrial chemical and endocrine disruptor, poses serious health risks, highlighting the need for sensitive detection met...

Immune cell-related gene signatures for diagnostic and prognostic stratification in thyroid cancer using machine learning analysis.

Bioactive Substances Characterization in Probiotic-Fermented Guava (Psidium guajava L.) Juice and Systematic Evaluation of its Anti-Hyperglycemic Activity.

The development of natural anti-hyperglycemic agents with minimal side effects is a critical objective in functional food research. This study compreh...

Endocrine hypertension in 2025: how AI and multiomics are revolutionizing detection.

INTRODUCTION: Endocrine hypertension (EH) represents a small yet clinically significant subset of secondary hypertension with curative potential. Rece...

Stacked ensemble learning and in-silico profiling reveal dual DPP-IV and SGLT2 inhibitors from Moringa oleifera metabolites.

Diabetes mellitus (DM) is a growing global health challenge, particularly in low-resource settings where access to effective therapies remains limited...

Identifying a fatty acid metabolic gene signature in diabetic cardiomyopathy through integrated bioinformatics and machine learning.

BACKGROUND: Diabetic cardiomyopathy (DCM) is a major cardiovascular complication of diabetes mellitus, ultimately progressing to heart failure and inc...

Hypoglycemia problem-solving ability as a key predictor of severe hypoglycemia: a machine learning approach in adults with type 1 diabetes.

AIMS/INTRODUCTION: Severe hypoglycemia (SH) is a major complication in adults with type 1 diabetes mellitus (T1DM). The multifactorial etiology of T1D...

A machine learning model for optimizing treatment of patients with poorly controlled type 2 diabetes.

BACKGROUND: Cardiorenal-protective sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) lack se...

R-GAT: cancer document classification leveraging graph-based residual network for scenarios with limited data.

Accurate classification of cancer-related biomedical abstracts is critical for advancing cancer informatics and supporting decision-making in healthca...

Application of machine learning approaches to develop predictive models for diabetes and hypertension among Bangladeshi Adults.

With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs), including hypertension and diabetes, pose signi...

Diethyl Phthalate (DEP) as a potential osteosarcoma risk factor: a multi-omics study integrating network Toxicology, single-cell RNA sequencing, and molecular docking.

Diethyl phthalate (DEP), a common plasticiser and endocrine disruptor, has been linked to cancer, but its role in osteosarcoma (OS) remains unclear. T...

Exploring estrogen synthesis and metabolism related markers and immune dynamics in osteoporosis-insights from single-cell RNA sequencing and Mendelian randomization.

BACKGROUND: Osteoporosis (OP) is characterized by decreased bone mineral density and an increased fracture risk, often due to declining sex hormone le...

Comparable survival after lobectomy and total thyroidectomy for T3b differentiated thyroid carcinoma: A population-based study.

BACKGROUND: The 2025 American Thyroid Association guidelines recommend total thyroidectomy for all T3b differentiated thyroid carcinoma (DTC). However...

Exploratory identification of COL1A1 as a potential gene linking endocrine-disrupting chemicals and lung adenocarcinoma: a bioinformatics and machine learning analysis.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are common environmental pollutants that affect human health. These chemicals have been linked to th...

Smart insulin dosage software based on trend arrows: an effective method for controlling hyperglycemia in hospitalized diabetic patients in non-endocrine departments (a randomized controlled trial).

Epidemiological Trajectories and Quality of Care Disparities of MASLD in Asia, 1990-2023.

BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated steatotic liver disease (MASLD) across Asia from 1990...

Spatial proteomics and machine learning reveal diagnostic protein signatures for indeterminate thyroid nodules: promising yet preliminary biomarkers requiring clinical validation.