Obstetrics & Gynecology

Validation of conformal prediction in cervical atypia classification.

Deep learning based cervical cancer classification can potentially increase access to screening in low-resource regions. However, deep learning models are often overconfident and do not reliably reflect diagnostic uncertainty. Moreover, they are typically optimized to generate maximum-likelihood predictions, which fail to convey uncertainty or ambiguity in their results. Such challenges can be add...

Effect of PET-MPs exposure on the toxicology of PCOS: a multi-platform computational toxicology investigation.

Polyethylene terephthalate microplastics (PET-MPs) function as endocrine-disrupting agents that interfere with steroidogenesis and folliculogenesis, potentially contributing to polycystic ovary syndrome (PCOS). This study integrates computational toxicology and machine learning to delineate the mechanisms linking PET-MP exposure to PCOS pathogenesis. We conducted systematic multi-omics analysis by...

Recent Advances in the Non-viral Delivery of Genes to Central Nervous System Disorders.

Disorders of the central nervous system (CNS), neurological disorders, neurodegenerative disorders, genetic disorders) constitute a significant burden...

Integrated single-cell and bulk transcriptomics reveals STAB1 as a novel therapeutic target for ovarian cancer.

The immunosuppressive tumor microenvironment (TME) and intrinsic heterogeneity of ovarian cancer (OC) are primary drivers of therapeutic resistance an...

Enhancing Exploration and Exploitation in Tumor Treatment Through Action-Guided Deep Reinforcement Learning.

Inverse treatment planning is pivotal in tumor treatment planning. It enables the multi-objective optimization of radiation dose delivery, ensuring pr...

Artificial intelligence models for osteoporosis risk prediction in postmenopausal women with CKD: A cross-sectional analysis of NHANES 2005 to 2018.

Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...

Classification of histological types in ovarian cancer using deep learning.

BACKGROUND: Histological typing of carcinomas is crucial considering the varying progression, prognosis, and treatment efficacy. Clear cell and mucino...

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 surgical data, including surgical motion, activity and pr...

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 is widely used for imaging adnexal masses, yet co...

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, tungiasis and cutaneous larva migrans-affect millio...

mRNA-based cancer vaccines: A new frontier in personalized immunotherapy.

The advancement of mRNA technology has rejuvenated the cancer treatment immunotherapy field by providing a flexible and scalable platform to generate ...

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 lipid spatial conformation in organ targeting and end...

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) metastasis, significantly increasing the risk of...

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 homeostasis. However, most currently available Lactobacillus...

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 is at a pivotal moment for the strategic implementa...

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 with locally advanced cervical cancer (LACC) recei...

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 associated with poor prognosis and provides key in...

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 for improving patient treatments. Extracellular ve...

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

Postpartum depression (PPD) is a widespread mental illness after delivery, which has a substantial impact on the health of both mothers and infants. M...