Obstetrics & Gynecology

Beyond the Coronaries: Utility of Extra-Coronary Calcification for Cardiovascular Risk Assessment in Women.

PURPOSE OF REVIEW: Globally, cardiovascular disease (CVD) is the leading cause of mortality in women. Traditional risk calculators underestimate atherosclerotic cardiovascular disease risk (ASCVD), particularly in women classified as low or intermediate risk. While coronary artery calcium scoring improves risk stratification, it remains underutilized in practice. Extra-coronary calcification (ECC)...

An Artificial Intelligence Model for the Automatic Classification of the Cervical Vertebral Maturation Stages.

OBJECTIVE: To develop an artificial intelligence (AI) model for automatic classification of cervical vertebral maturation (CVM) stages on lateral cephalometric radiographs (LCR). MATERIALS AND METHODS: Overall, 1140 LCRs were labeled and classified according to the CVM user guide by McNamara and Franchi using a two-stage pipeline. In the first stage, the LCRs were cropped to extract the region of ...

Early identification of major depression risk among reproductive-age women using hormonal contraceptives in southern Ethiopia: A Machine Learning Approach.

Machine-learning (ML) algorithms are increasingly valuable in health sciences because they can analyze complex, high-dimensional data and detect patte...

Research progress and development strategies of antibody-oligonucleotide conjugates.

Antibody-oligonucleotide conjugates (AOCs) effectively integrate the delivery capability of antibodies with the specific gene regulatory function of o...

Structure-based machine learning model for discovering pregnane X receptor (PXR) agonists and biological activity validation.

Pregnane X receptor (PXR), a nuclear receptor superfamily member, maintains bile acid homeostasis by regulating metabolic enzymes [e.g., cytochrome P4...

MicroRNAs in endometriosis: bioinformatics resources, machine learning strategies, and multi-omics perspectives.

BACKGROUND: Endometriosis is a heterogeneous gynecological disorder characterized by chronic pain, infertility, and substantial impairment of quality ...

Platelets as Programmable Drug Depots: Toward Predictive and Mechanistic Drug Loading.

Efficient drug delivery remains a major challenge in pharmaceutical science, with synthetic nanocarriers often facing limitations in real biological s...

Molecular and spatial differences in the tumor microenvironment of high-grade serous ovarian cancers with short versus long-term survival.

OBJECTIVE: Survival of patients diagnosed with advanced-stage high-grade serous ovarian cancer (HGSOC) varies widely. Understanding the biological and...

[Application analysis of the artificial intelligence model DeepSeek in breast cancer treatment decision-making].

Objective: To evaluate the accuracy and feasibility of applying the DeepSeek artificial intelligence model in clinical decision-making for breast canc...

The progesterone to estradiol ratio predicts fear extinction in mice and humans.

Sex differences in fear memory are well documented, yet the role of menstrual cycle phases and ovarian hormone dynamics remains unclear. Here, we inve...

Machine learning identification of maternal inflammatory response and systemic inflammatory response from placental membrane whole slide images.

INTRODUCTION: The placenta forms a critical barrier to infection through pregnancy, labor and, delivery. Acute placental inflammation in the membranes...

Development of an interpretable machine learning model for predicting stress urinary incontinence following the delivery of a first child.

INTRODUCTION: The goal of this research is to use machine learning (ML) techniques to create a risk prediction model for postpartum stress urinary inc...

Integrating AI into hospital workflows: implementation strategies and real-world barriers.

Artificial intelligence (AI) is increasingly being integrated into hospital systems with the potential to transform clinical workflows, operational ef...

Comparative evaluation of conventional radiomics and VGG-SAM fusion strategies for MRI-based preoperative prediction of perineural invasion in cervical cancer.

OBJECTIVE: Perineural invasion (PNI) is an adverse feature in cervical cancer and may influence nerve-sparing surgery. We compared conventional radiom...

Performance comparison between a deep learning model and spine surgeons in detecting cervical spinal cord compression on radiographs.

OBJECTIVE: This study aimed to develop a deep learning (DL) model for the detection of cervical spinal cord compression on cervical radiographs and co...

Identification of Cervical Cancer Biomarkers Using Gene Co-Expression Networks and Machine Learning Methods.

Cervical cancer (CC) causes significant mortality due to late diagnosis and limited understanding of its molecular drivers. The complex gene co-expres...

Toward an Ethical Framework for Patient-Facing Artificial Intelligence in Clinical Settings.

Patient-facing artificial intelligence in clinical settings raises distinct ethical challenges that require explicit attention as patients transition ...

From Report to Record: Prompt-Based Information Extraction from Gynecology Oncology Reports Using LLMs.

The growing capabilities of Large Language Models (LLMs) in understanding and generating clinical text are transforming the processing of unstructured...

A Real-Time Clinical Text Information Extractor via LLM.

The extraction of structured information from unstructured clinical text is a critical requirement for real-time decision support and research applica...

Integration and Harmonization of Multi-Source Obstetric Data Using Rule-Based NLP for Fetomaternal Risk Modelling.

More than 80% of pregnancies in Germany are classified as high risk, leading to inefficient resource allocation. Although data-driven approaches could...