Obstetrics & Gynecology

Deep learning for Evaluation and Prediction of TecHnical Skills in robotic-assisted vaginal cuff closure (DEPTHS) study.

BACKGROUND: To support surgical education, there has been an increasing focus on integrating surgica...

A Deep Learning Framework for Enhanced Ovarian Adnexal Mass Classification Using Routinely Acquired Ultrasound Images.

Accurate classification of ovarian masses is crucial for clinical decision-making. B-mode ultrasound...

Operationalising One Health for epidermal parasitic skin diseases: threshold-triggered mass drug administration and a minimal indicator set.

Epidermal parasitic skin diseases (EPSDs)-including scabies, pediculosis, cutaneous leishmaniasis, t...

Artificial intelligence-guided design of LNPs for in vivo targeted mRNA delivery via analysis of the spatial conformation of ionizable lipids.

Efficient mRNA delivery to specific tissues requires optimized ionizable lipids, yet the role of lip...

LymphUs: A multicenter open-access database of lymph node ultrasound images in patients with papillary thyroid carcinoma for clinical and artificial intelligence research.

Approximately 30-50% of Papillary thyroid carcinoma (PTC) patients develop cervical lymph nodes (LNs...

Machine learning-based prediction of BV-relevant probiotic functional potential in vaginal-derived Lactobacillus crispatus strains.

The vaginal microbiota plays a pivotal role in maintaining female reproductive health and homeostasi...

Managing maternity: Moving care, not patients, using artificial intelligence (AI), internet-of-things (IOT) and point-of-care testing (POCT) devices.

The integration of artificial intelligence (AI) into healthcare is accelerating and maternity care i...

Unsupervised clustering analysis unravels the role of systemic inflammatory indices in the prognosis of patients with locally advanced cervical cancer treated with chemoradiation.

BACKGROUND AND PURPOSE: This study aimed to predict the treatment outcomes and survival of patients ...

Explainable tabular deep learning models for antenatal cesarean delivery prediction in multiparous women.

Comprehensive Multiomics Characterization of Perineural Invasion in Cervical Cancer Reveals Diagnostic Markers, Molecular Drivers, and Therapeutic Strategies.

UNLABELLED: Perineural invasion (PNI) is an important pathologic feature of cervical cancer that is ...

An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3.

The early and precise diagnosis of gynecological malignancies, such as cervical cancer, is critical ...

Machine learning-based methods for predicting postpartum depression: A review.

Postpartum depression (PPD) is a widespread mental illness after delivery, which has a substantial i...

Association of inflammatory biomarkers during pregnancy and the postpartum period with the risk of postpartum anxiety symptoms.

BACKGROUND: Inflammation is pivotal in psychiatric pathophysiology, yet evidence linking inflammator...

Artificial intelligence-enabled personalisation of oral drug delivery: From data-driven design to on-demand manufacturing.

Artificial intelligence (AI) is reshaping pharmaceutical research by enabling data-intensive tasks t...

Homologous recombination deficiency in Ovarian cancer: The game-changer for first-line maintenance therapy.

Homologous recombination deficiency (HRD) plays a central role in the pathogenesis and therapeutic v...

PETWB-REP: A Multi-Cancer Whole-Body FDG PET/CT Dataset with Corresponding Radiology Reports.

Publicly available, large-scale medical imaging datasets are crucial for developing and validating a...

Deep learning based gestational age estimation from multi-view fetal brain magnetic resonance imaging.

BACKGROUND: Gestational age (GA) is essential for assessing fetal development, but conventional meth...

A Semi-Automated Deep Learning Model for Diagnosing Placenta Accreta Spectrum (COMPAS): Comparison with Radiologists' Interpretations.

Multimodal MRI radiomics for predicting HIFU ablation efficacy in uterine fibroids: a machine learning study.

OBJECTIVE: To explore the predictive value of machine learning-based multimodal MRI radiomics combin...

Microfluidic electroporation for drug and gene delivery: Driving innovation from single-cell precision to high-throughput preclinical and therapeutic platforms.

Intracellular delivery of therapeutic biomolecules represents a fundamental prerequisite for cell-ba...

Artificial intelligence-assisted spatial omics-based biomimetic nanoplatform for intelligent and precise intervention in the immunosuppressive core region of ovarian cancer.

Ovarian cancer (OC) ranks among the most aggressive malignancies of the female reproductive system. ...