Endocrinology

Interpretable machine learning based on intratumoral and peritumoral ultrasound radiomics for predicting central lymph node metastasis in papillary thyroid carcinoma.

OBJECTIVES: This retrospective and single-center study aimed to develop machine learning (ML) model integrating clinical features, ultrasound (US) features, and radiomics signatures extracted from both intratumoral and peritumoral regions to predict central lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC). The SHapley Additive exPlanations (SHAP) method was applied to visualize th...

Spatiotemporal Remodeling of Bone as a Reversibly Adaptive Biological Material in Djungarian Hamsters under Regulated Photoperiod Conditions.

Bone loss in humans is typically progressive and difficult to reverse, posing challenges for both pharmacological therapy and the long-term performance of bone replacement materials. Photoperiod-sensitive species such as the Djungarian hamster undergo cyclical physiological adaptations in response to seasonal light cues, providing a unique framework to investigate bone adaptation during physiologi...

Diagnostic model and identification of IGFBP2 as an aging-related biomarker and therapeutic target for systemic sclerosis-associated interstitial lung disease through integrated bioinformatics and machine learning approaches.

BACKGROUND: Cellular senescence is a critical contributor to the pathogenesis of systemic sclerosis-associated interstitial lung disease (SSc-ILD). Ho...

Mechanistic signatures of comorbid PTSD with cognitive impairment implicate cortisol-induced neural toxicity.

The men and women who worked in rescue and recovery operations at the 9/11 World Trade Center site are developing cognitive impairment (CI) at mid-lif...

Leveraging natural language processing and machine learning to identify chronic conditions from primary care electronic medical records.

Primary care electronic medical records (EMRs) contain rich data that can support proactive identification of chronic health conditions. However, leve...

From Observation to Prediction: Machine Learning Analysis of Progression of Visual loss in Nonarteritic Anterior Ischemic Optic Neuropathy.

OBJECTIVE: To determine whether combinations of modifiable clinical/systemic risk factors and structured trial variables predict early disease progres...

AFTS: A patient-agnostic encoder-decoder architecture with directional attention for blood glucose forecasting.

Accurate blood glucose forecasting remains challenging due to inter-patient heterogeneity and complex glycemic dynamics. We present AFTS (Adaptive Fea...

Sleep Disorders and Male Infertility: Integrated Mechanisms and Precision Therapeutic Strategies.

BACKGROUND: Male factor infertility accounts for nearly half of infertility cases worldwide, yet modifiable lifestyle-related risk factors remain insu...

Phenotypic clustering of cardiovascular risk profiles in systemic lupus erythematosus.

ObjectiveThis study aimed to identify distinct cardiovascular risk phenotypes in systemic lupus erythematosus (SLE) using an unsupervised cluster anal...

Establishment of insulin resistance-related ten-gene signature in endometrial cancer and identification of ACTL8 as a prognostic and immunological biomarker.

BACKGROUND: Endometrial cancer (EC) is a common gynecological tumor. Insulin resistance (IR) increases the risk of EC. However, the common molecular b...

Artificial intelligence on opportunistic computed tomography for predicting vertebral fracture risk in women undergoing estrogen deprivation therapy for breast cancer.

PURPOSE: Fracture risk prediction in women exposed to hormone deprivation therapies (HDTs) for breast cancer is challenging, since bone mineral densit...

Training the diagnostic artificial intelligence in thyroid sonography: how well is deep learning truly learning?

INTRODUCTION: The use of artificial intelligence (AI) for TI-RADS classification in neck sonography for the assessment of thyroid nodules has been pro...

A Comprehensive Approach to Days' Supply Estimation in a Real-World Prescription Database: Algorithm Development and Validation Study.

BACKGROUND: For accurate medication usage statistics and medication adherence calculations, we need to have an accurate days' supply (DS) for each pre...

The contribution of phenolic endocrine-disrupting chemicals to breast cancer risk: A comprehensive bioinformatics analysis.

Periodontitis Prediction Model Using Linked Electronic Health and Dental Records.

INTRODUCTION: Periodontal disease (PD) is closely linked to systemic health, with established associations with chronic conditions (eg, diabetes, card...

Limitation of existing GFR estimating equations and application of artificial intelligence in improving GFR estimation and chronic kidney disease progression in people with diabetes.

The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation is the most commonly used equation for estimating glomerular filtration ...

Data-driven subgroups for 3-year risk stratification of incident diabetes and complications in diabetes-free Chinese adults.

BACKGROUND: Substantial metabolic heterogeneity exists prior to the development of diabetes, creating opportunities for earlier and more precise inter...

A Cross-Sectional Study Based on Deep Learning to Explore the Effect of Triglyceride/Glucose Index on Periodontitis: An Analysis Based on the Large NHANES Database.

PURPOSE: Periodontitis is a common chronic inflammatory disease closely associated with metabolic syndrome. The triglyceride-glucose (TyG) index is a ...

Enhanced diabetes prediction using pre-trained CNNs, LSTM, and conditional GAN on transformed numerical data.

Diabetes remains a major public health challenge, contributing to complications such as kidney disease, cardiovascular disorders, and diabetic retinop...

HLA-DPA1 as a diagnostic biomarker differentiating early- and late-onset preeclampsia.

The occurrence and development of a wide range of preeclampsia (PE), especially early-onset preeclampsia (EOPE), is closely associated with the immune...