Endocrinology

Predictive models for the occurrence and lymph node metastasis of papillary thyroid carcinoma with regional risk heterogeneity.

Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, and cervical lymph node met...

Integrating Sperm Microscopy, Environmental Exposures, and Lifestyle Factors for Male Fertility Analysis: Protocol for the Nippon Semen and Environmental Exposure Database (N-SEED) Cross-Sectional Study.

BACKGROUND: Conventional semen analysis does not fully capture male reproductive potential. The sper...

Predictive Model for Mild Autonomous Cortisol Secretion in Patients Evaluated in Artificial Intelligence-Driven Adrenal Incidentaloma Clinic.

BACKGROUND: Mild autonomous cortisol secretion (MACS) is present in approximately 20% to 50% of adre...

Cancer cachexia: A tumor-driven disorder of whole-body homeostasis.

Cancer cachexia is a systemic metabolic syndrome driven by tumor-induced disruption of whole-body ho...

Diagnostic Accuracy of Ultrasound Radiomics for Cervical Lymph-Node Metastasis in Papillary Thyroid Carcinoma: Evidence Predominantly From Chinese Cohorts.

Pre-operative identification of cervical lymph-node metastasis (LNM) guides surgical extent in papil...

A vision-language foundation model improves preoperative diagnosis of follicular thyroid neoplasms using ultrasound images.

Preoperative discrimination between follicular thyroid carcinoma (FTC) and follicular thyroid adenom...

Region-guided decoupled fusion network for ultrasound-based classification of thyroid nodules with and without Hashimoto's thyroiditis.

RATIONALE AND OBJECTIVES: Differentiating benign from malignant thyroid nodules is particularly chal...

Unveiling varietal specificity in non-destructive grape quality monitoring: Explainable AI and feature selection for sugar and organic acid prediction using NIR spectroscopy.

Sugar and organic acid content are crucial factors determining grape quality. Non-destructive testin...

The predictive value of serological markers for successful weaning and 30-day mortality in patients with severe intracerebral hemorrhage.

AIM: This study intends to screen serological indicators related to weaning outcomes and 30-day mort...

Speaking Patient's Language: Assessment of Readability and Fidelity of Artificial Intelligence-Optimized Consent Forms.

INTRODUCTION: Informed consent requires patients to fully comprehend the risks, benefits, and altern...

A scale-down mini-bioreactor for the acceleration of data-driven bioprocess optimisation in cell therapy.

Cell therapies have demonstrated great potential for treating a broad range of diseases where conven...

Current Controversies in Acromegaly Care.

Persistent disease after surgery for acromegaly is common. Expanding medical management options impr...

System-level clustering of testosterone-related biomarkers identifies high-risk aging profiles linked to inflammation and renal function.

BACKGROUND: Serum total testosterone (TT) interacts with multiple physiological systems and is impli...

Multi-site validation of an AI-based biomarker test for determining ER, PR, and HER2 status from H&E-stained breast cancer slides.

BACKGROUND: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth fac...

Identification and Validation of Transcriptomic Signatures in Inflammatory Bowel Disease with Metabolic Syndrome via Bioinformatics and Machine Learning.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic, nonspecific inflammatory disorder affecti...

Deep Learning-Based Multimodal Fusion of Ultrasound, Cytology, and Clinical Features to Distinguish Follicular Thyroid Carcinoma from Adenoma: A Multicenter Study.

RATIONALE AND OBJECTIVES: Preoperative differentiation between follicular thyroid carcinoma (FTC) an...

Use of Continuous Glucose Monitoring With Machine Learning to Identify Metabolic Subphenotypes and Inform Precision Lifestyle Changes.

The classification of diabetes and prediabetes by static glucose thresholds obscures the pathophysio...

Differentiation of adrenal metastases and adenomas based on clinical characteristics, deep learning features, and radiomics features derived from ultrasound imaging.

Analysis of B-Scan Ultrasonography Using Neural Networks to Predict Risk of Fibrosis in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD).

OBJECTIVE: The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) contin...

Exploring Metabolic Changes in Children with Congenital Hypothyroidism: A Serum Metabolomic Study Combined by Machine Learning.

Congenital hypothyroidism (CH) is a genetic endocrine disorder that can cause developmental delays i...

Diabetes Technology: An Update.

Diabetes is one of the most prevalent chronic diseases worldwide, with rates that continue to increa...