Endocrinology

Radiomics and machine learning analysis of ultrasound images in Bethesda IV thyroid nodules: a retrospective monocentric study.

Bethesda IV thyroid nodules remain a major diagnostic challenge because cytology cannot reliably distinguish benign from malignant follicular-patterned lesions, often leading to diagnostic surgery for ultimately benign disease. This study evaluated whether ultrasound radiomics combined with machine learning could improve preoperative risk stratification in this setting. We conducted a retrospectiv...

Automated segmentation of thyroid tissue and carotid artery in ultrasound videos using expert-in-the-loop deep learning: a foundational step toward AI-assisted thyroid diagnostics.

Ultrasound (US) is the primary imaging modality for thyroid evaluation, yet its diagnostic accuracy remains highly operator dependent. Automated identification of thyroid anatomy and adjacent vascular structures may improve standardisation, support image-guided procedures, and enhance preoperative decision-making in endocrine surgery. In this study, 300 B-mode ultrasound videos from 280 patients (...

Development and validation of a nomogram for predicting hemoptysis risk in patients with bronchiectasis: A study based on Random Forest algorithm.

Hemoptysis is a severe and potentially life-threatening complication of bronchiectasis. There is currently a lack of reliable tools for the individual...

Skeletal muscle reprogramming of metabolic, ribosomal and developmental pathways contributes to Roux-en-Y gastric bypass-induced adaptation in women.

BACKGROUND: Understanding how skeletal muscle responds to weight loss is crucial for developing targeted strategies to manage obesity and promote sust...

Mitochondria-associated protein UQCRH serves as a potential target in mild cognitive impairment of type 1 diabetes mellitus mice.

Type 1 diabetes mellitus (T1DM) and cognitive impairment (CI) are diseases impacting human health. Mild cognitive impairment (MCI), a critical stage o...

Joint Multi-Task Deep Learning with Cross-Task Attention for Simultaneous Lesion Segmentation, Detection, and Severity Grading of Diabetic Retinopathy on Fundus Images: An External Validation Study.

BACKGROUND: Diabetic retinopathy (DR) severity is graded from the type and distribution of retinal lesions, yet most automated methods address grading...

Predictors of atrial fibrillation recurrence after catheter ablation: a systematic review.

BACKGROUND: Recurrence of atrial fibrillation (AF) following catheter ablation is a major clinical problem, and there is considerable variability in p...

Development of a machine learning-based noninvasive diagnostic model for liver fibrosis in metabolic-associated steatotic liver disease.

BACKGROUND: To address the lack of simple tools for assessing fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD), this study...

AI-derived oocyte morphology and follicular fluid biomarkers in donors.

Oocyte quality is a key determinant of reproductive success, yet its assessment in assisted reproduction largely relies on subjective morphological cr...

Content-based retrieval of fundus images and diabetic retinopathy detection using variants of local texture features.

Content-based retinal image analysis plays a crucial role in the early diagnosis of ocular diseases. In this study, we proposed a novel approach for e...

Neural networks improve repeatability of intravoxel incoherent motion (IVIM) parameter estimation in pancreatic diffusion-weighted MRI.

Intravoxel incoherent motion (IVIM) analysis in diffusion-weighted MRI (DWI-MRI) shows potential for characterizing pancreatic tissue, but its clinica...

Identification of key biomarkers for ferroptosis in diabetic kidney disease using machine learning and WGCNA.

OBJECTIVE: Early detection of diabetic kidney disease (DKD) remains challenging because currently available clinical markers mainly reflect establishe...

The Metabolite indole-3-acetic acid of Bacteroides ovatus ameliorates ovariectomy-induced bone loss by activating AhR and inhibiting oxidative stress.

Postmenopausal osteoporosis represents a systemic skeletal condition distinguished by diminished bone mass and heightened skeletal fragility. Emerging...

The hard exudate pathway: Biological mechanisms, imaging correlates, and clinical implications.

Hard exudates are common fundus findings in retinal vascular disease, but are frequently regarded as passive remnants of vascular leakage rather than ...

Use of heart rate variability in prediction of clinical deterioration in critically ill hospitalised adults: a systematic review protocol.

INTRODUCTION: Heart rate variability (HRV) is a measurement derived from the beat-to-beat variation in heart rate and reflects the complex interaction...

Perceptions of simulated artificial intelligence in medical consultations: associations with stress, memory, and perceived credibility.

The growing integration of digital technologies into healthcare requires understanding the impact of different consultation modalities on patient stre...

Explainable AI-Assisted Multimodal Ultrasound Radiomics for Preoperative Risk Stratification of Central Lymph Node Metastasis in Papillary Thyroid Carcinoma.

The objective was to develop and validate an explainable artificial intelligence (AI)-based multimodal approach for preoperative risk stratification o...

A Thyroid Nodule Differentiation Model for Benign-Malignant Identification by Fusing Transfer Learning and Gradient Boosting Decision Tree.

Accurate identification of benign and malignant thyroid nodules is a core link in clinical diagnosis and treatment decision-making, which directly aff...

Organelle proteomics of human, neonatal pig, healthy and diabetic mouse islets.

Pancreatic islets, in which β cells constitute 50%-80% of the endocrine mass, are the body's site for glucose-regulated insulin secretion. Pancreatic ...

The role of machine learning in early detection, accurate diagnosis, and timely treatment of diseases.

The contemporary healthcare landscape is experiencing a significant transformation driven by the rapid growth of digital health data and advancements ...