Obstetrics & Gynecology

The utility of low-dose pre-operative CT of ovarian tumor with artificial intelligence iterative reconstruction for diagnosing peritoneal invasion, lymph node and hepatic metastasis.

PURPOSE: Diagnosis of peritoneal invasion, lymph node metastasis, and hepatic metastasis is crucial in the decision-making process of ovarian tumor treatment. This study aimed to test the feasibility of low-dose abdominopelvic CT with an artificial intelligence iterative reconstruction (AIIR) for diagnosing peritoneal invasion, lymph node metastasis, and hepatic metastasis in pre-operative imaging...

Development of macrophage M2 relate signature for predicting prognosis and immunotherapy response in ovarian cancer.

BACKGROUND: Ovarian cancer ranks as the fifth most common cause of cancer-related deaths in women worldwide. Macrophages M2 is believed to support tumor growth by suppressing immune responses and promoting angiogenesis.

Machine learning in ovarian cancer: a bibliometric and visual analysis from 2004 to 2024.

OBJECTIVE: Ovarian cancer (OC) is a common malignant tumor in women, with poor prognosis and high mortality rates. Early diagnosis, screening, and pro...

DEMAC-Net: A Dual-Encoder Multiattention Collaborative Network for Cervical Nerve Pathway and Adjacent Anatomical Structure Segmentation.

OBJECTIVE: Currently, cervical anesthesia is performed using three main approaches: superficial cervical plexus block, deep cervical plexus block, and...

Leveraging neighborhood-level Information to Improve Model Fairness in Predicting Prenatal Depression.

IMPORTANCE: Perinatal depression (PND) affects 10-20% of pregnant women, with significant racial disparities in prevalence, screening, and treatment. ...

Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer.

BACKGROUND: The study aimed at developing and validating a deep learning (DL) model based on the ultrasound imaging for predicting the platinum resist...

Supervised machine learning for predicting drug release from acetalated dextran nanofibers.

Electrospun drug-loaded polymeric nanofibers can improve the efficacy of therapeutics for a variety of implications. By design, these biomaterial plat...

Autonomous Robotic Pruning in Orchards and Vineyards: a Review

Manual pruning is labor intensive and represents up to 25% of annual labor costs in fruit production, notably in apple orchards and vineyards where ...

Next-generation Approaches in Targeting Polycystic Ovarian Syndrome: Innovative Strategies.

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder that affects millions of women worldwide and is characterized by ovarian dysfunction,...

Systems-level Insights to Improve Prenatal Detection of Congenital Heart Disease: Emotional Intelligence Today, Artificial Intelligence Tomorrow.

High throughput recurrent pregnancy loss screening: urine metabolic fingerprints LDI-MS and machine learning.

Infertility is a significant challenge faced by many families worldwide, with recurrent pregnancy loss (RPL) being a prevalent cause of infertility am...

Pan-cancer predictive survival model development and evaluation using electronic health record and genetic data across 10 cancer types.

The growing burden of cancer and recent surge in healthcare data availability call for new ways of analysing this multifactorial disease and improving...

Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis.

BACKGROUND: CD8T cells, also known as cytotoxic T lymphocytes, play a key role in the tumor immune microenvironment (TME) and immune response. The aim...

Unraveling the molecular mechanisms of paclitaxel in high-grade serous ovarian cancer through network pharmacology.

High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of epithelial ovarian cancer, often diagnosed at advanced stages wi...

Random forest-based model for the recurrence prediction of borderline ovarian tumor: clinical development and validation.

PURPOSE: This study aims to develop an effective machine learning (ML)-based predictive model for the recurrence of borderline ovarian tumor (BOT), an...

A novel scheme for non-invasive drug delivery with a magnetically controlled drug delivering capsule endoscope.

There is a lack of effective means for precise drug delivery of gastrointestinal diseases. Herein we report a novel magnetically controlled drug deliv...

Lipid nanoparticle (LNP) mediated mRNA delivery in neurodegenerative diseases.

Neurodegenerative diseases (NDD) are characterized by the progressive loss of neurons and the impairment of cellular functions. Messenger RNA (mRNA) h...

Role of Neck Pain in Defining Clinical Trajectories of Outcomes in Patients With Degenerative Cervical Myelopathy: Results of a Novel Machine Learning Algorithm.

Study DesignRetrospective analysis of prospective data.ObjectivesNeck pain represents a crucial factor underscoring a patient's decision to receive su...

Multi-Task Collaborative Assisted Training Method for Grouping Fuzzy Categories Classification of Cervical Cancer Cells.

Cervical cancer is a malignant tumor that endangers women's life and health. While deep learning has enhanced the accuracy of cervical cell classifica...

Recent advances in multimodal approaches for investigating placental development and related diseases.

The placenta is a vital organ that supports fetal growth and pregnancy maintenance. Its dysfunction is associated with severe complications, including...