Pregnancy

Prediction of Central Lymph Node Metastasis in Papillary Thyroid Carcinoma Using Multi-Ultrasound Radiomics of Intratumoral and Peritumoral Regions.

OBJECTIVE: The aim of this study was to integrate multimodal intratumoral and peritumoral ultrasound radiomic features with clinical data to construct a predictive model for central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) and to explore its clinical utility. METHODS: A total of 470 PTC patients who underwent 2-dimensional (2D) ultrasound, color Doppler flow ...

An interpretable machine learning model integrating ultrasound and clinical variables for predicting osteoporosis in patients with rheumatoid arthritis.

OBJECTIVES: Rheumatoid arthritis (RA) significantly increases the risk of osteoporosis (OP) and fractures, yet dual-energy X-ray absorptiometry (DXA) is underused in routine care. This study aims to develop and explain a machine learning model to identify individuals with OP risk among RA patients. METHODS: In this single-center retrospective study, 299 RA patients were enrolled and split 7:3 into...

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on...

Automated early preterm detection using hybrid multimodal attention network with gated fusion.

Preterm birth is a major pregnancy complication associated with increased maternal and neonatal risks, making early detection of labor essential. Elec...

Current Perspectives on Thyroid Nodule Evaluation: Integrating Cytomorphology, Ultrasound Risk Stratification, and Molecular Testing.

Fine-needle aspiration biopsy (FNAB) remains the cornerstone of preoperative evaluation of thyroid nodules and represents one of the most enduring and...

Multimodal Deep Fusion of Ultrasound Images and Clinical Factors for Pre-operative Prediction of Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma.

OBJECTIVE: Lateral cervical lymph node metastasis (LLNM) is missed in up to 30% of papillary thyroid carcinoma (PTC) patients pre-operatively, leading...

Correlation between artificial intelligence-based IDAScore and embryo morphokinetic parameters: a retrospective cohort study.

PURPOSE: The rapid advancement of artificial intelligence (AI) has brought new opportunities for embryo evaluation. The integration of AI with time-la...

Predicting placenta accreta spectrum antenatally: a deep learning-radiomics dual-model based on intraoperative clinical and histopathologic criteria.

PURPOSE: Definitive diagnosis of placenta accreta spectrum (PAS) disorders occurs at delivery by using combined intraoperative clinical and histopatho...

PatchGAN-guided semi-supervised U-Net for carotid plaque segmentation in ultrasound under limited annotation conditions.

OBJECTIVE: Artificial intelligence models are increasingly used for stroke risk evaluation and clinical decision-making. However, the scarcity of expe...

Machine Learning-Guided Near-Infrared Laser Processing for Precise Geometry Control in Microneedles with Downstream microLED-Triggered Photothermal Functionality.

Transdermal drug delivery and sensing provide non-invasive routes for localized therapy and biomarker detection. Microneedles (MNs) enable pain-free a...

A Generative Multi-modal Deep Learning Framework for Non-invasive Prediction of Ki-67 Expression in Papillary Thyroid Microcarcinoma Using Preoperative Ultrasound.

Accurate assessment of Ki-67 expression plays a critical role in the risk stratification and prognosis of papillary thyroid microcarcinoma (PTMC). How...

A Hybrid CNN-Transformer Model with Crossover Boosted Cheetah Optimization for Prenatal Spina Bifida Identification from Ultrasound Images.

OBJECTIVES: Spina bifida is a birth defect caused by the incomplete closure of the neural tube around the spinal cord. Earlier, various deep learning-...

A study on the influencing factors of perceived artificial intelligence substitution risk.

Artificial intelligence technologies are rapidly penetrating and reshaping the labor market. As a result, perceived AI substitution risk among workers...

Automated ventricular and midline segmentation in cranial ultrasound with metrology.

Ultrasound imaging through sonolucent cranial implants is an emerging modality for post-neurosurgical monitoring of the adult brain, but quantitative ...

A Noise-Aware Robustness Evaluation Framework for Breast Cancer Classification in Ultrasound Imaging.

Accurate detection of breast cancer is essential, as it remains a leading cause of cancer-related mortality worldwide. Ultrasound is adopted due to it...

Multi-component exercise intervention methods for intelligent assisted diagnosis of sarcopenia in the elderly based on deep learning.

Population aging has made sarcopenia a major public health challenge in geriatric medicine. Current clinical diagnosis relies on large specialized equ...

RCAF for patient-level thyroid ultrasound malignancy prediction under leakage-free evaluation and calibration.

Accurate differentiation between benign and malignant thyroid nodules on ultrasound remains clinically important, yet interpretation is operator-depen...

Multistage microrobots with pH-responsive release of platelet membrane-coated nanoparticles.

Targeted drug delivery in the gastrointestinal tract remains challenging because therapeutics must overcome multiple hierarchical barriers before reac...

Predicting preoperative lymph node metastasis of hilar cholangiocarcinoma based on deep learning radiomics.

BACKGROUND: The objective of this study was to evaluate whether deep learning radiomic (DLR) models utilizing B-mode ultrasound (BUS) and contrast-enh...

Precision-Driven Management of Great Saphenous Varicose Veins: A Narrative Review.

OBJECTIVES: Great saphenous vein (GSV) incompetence is common, but numerous treatment options complicate patient-treatment matching. This narrative re...