Endocrinology

Classification of Japanese type 1 diabetes based on clinical phenotypes and its association with diabetic complications: Across-sectional study.

INTRODUCTION: Despite the increasing number of studies using machine learning to develop individualized treatment strategies, only a few have been conducted in patients with type 1 diabetes. This study aimed to identify the characteristics of Japanese patients with type 1 diabetes, classified into subgroups using data-driven cluster analysis based on pancreatic beta-cell function, obesity, and gly...

Social and Structural Determinants of Lower Extremity Amputations in Diabetes.

PURPOSE OF REVIEW: Lower extremity amputations (LEAs) are among the most severe complications of diabetes, with approximately 1.5 million procedures performed globally each year. This review explores the impact of social and structural determinants of health on amputation rates in diabetic patients, highlighting disparities driven by systemic factors.

Differential Diagnosis of Papillary Thyroid Carcinoma and Nodular Goiter With Papillary Hyperplasia Using Hyperspectral Imaging Technology.

Papillary thyroid carcinoma (PTC) and nodular goiter with papillary hyperplasia (NGPH) share similar histological features, complicating both preopera...

Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.

In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block ...

Dynamic mode decomposition for analysis and prediction of metabolic oscillations from time-lapse imaging of cellular autofluorescence.

Oscillations are a common phenomenon in cell biology. They are based on non-linear coupling of biochemical reactions and can show rich dynamic behavio...

Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.

Breast cancer is the most prevalent and lethal form of cancer being the utmost common medical concern of women. Breast cancer etiology implicates nume...

Exploring the link between the ZJU index and sarcopenia in adults aged 20-59 using NHANES and machine learning.

Sarcopenia, characterized by progressive loss of muscle mass and function, is a growing public health concern. The ZJU index, a novel metabolic marker...

Integrating machine learning and bioinformatics approaches to identify novel diagnostic gene biomarkers for diabetic mice.

Diabetes is a complex metabolic disorder, and its pathogenesis involves the interplay of genetic, environmental factors, and lifestyle choices. With t...

Improved bio-inspired with machine learning computing approach for thyroid prediction.

Thyroid illness is widely recognised as a prevalent health condition that can result in a range of health disorders. Thyroid illnesses, namely hypothy...

Detection of fasting blood sugar using a microwave sensor and convolutional neural network.

Monitoring of fasting blood sugar (FBS) is a critical component in the diagnosis and management of diabetes, one of the most widespread chronic diseas...

Therapeutic horizons in metabolic dysfunction-associated steatohepatitis.

Metabolic dysfunction-associated steatohepatitis (MASH), the progressive inflammatory form of MASLD, is now a leading cause of chronic liver disease w...

Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.

BACKGROUND: Since the discovery of the life-saving hormone insulin in 1921 by Dr Frederick Banting in 1921, there have been many critical discoveries ...

A Multimodal Predictive Model for Chronic Kidney Disease and Its Association With Vascular Complications in Patients With Type 2 Diabetes: Model Development and Validation Study in South Korea and the U.K.

OBJECTIVE: To develop a multimodal model to predict chronic kidney disease (CKD) in patients with type 2 diabetes mellitus (T2DM), given the limited r...

Orbital CT deep learning models in thyroid eye disease rival medical specialists' performance in optic neuropathy prediction in a quaternary referral center and revealed impact of the bony walls.

PURPOSE: To develop and evaluate orbital CT deep learning (DL) models in optic neuropathy (ON) prediction in patients diagnosed with thyroid eye disea...

Ultrasound-based classification of follicular thyroid Cancer using deep convolutional neural networks with transfer learning.

This study aimed to develop and validate convolutional neural network (CNN) models for distinguishing follicular thyroid carcinoma (FTC) from follicul...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool...

Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy.

Metabolic homeostasis requires engagement of catabolic and anabolic pathways consuming nutrients that generate and consume energy and biomass. Our cur...

A supervised machine learning approach with feature selection for sex-specific biomarker prediction.

Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for ...

Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis.

Early detection of thyroid cancer improves patient survival rate from 51.9% to 99.9%. Fine needle aspiration cytology is the primary method for diagno...

Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer.

Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM), yet the shared molecular ...