Obstetrics & Gynecology

Latest AI and machine learning research in obstetrics & gynecology for healthcare professionals.

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Showing 316-336 of 2,417 articles
Prediction of postpartum depression in women: development and validation of multiple machine learning models.

BACKGROUND: Postpartum depression (PPD) is a significant public health issue. This study aimed to de...

Interstitial-guided automatic clinical tumor volume segmentation network for cervical cancer brachytherapy.

Automatic clinical tumor volume (CTV) delineation is pivotal to improving outcomes for interstitial ...

NLP-driven integration of electrophysiology and traditional Chinese medicine for enhanced diagnostics and management of postpartum pain.

Postpartum pain encompasses a range of physical and emotional discomforts, often influenced by hormo...

Leveraging swin transformer with ensemble of deep learning model for cervical cancer screening using colposcopy images.

Cervical cancer (CC) is the leading cancer, which mainly affects women worldwide. It generally occur...

A deep learning approach to understanding controlled ovarian stimulation and in vitro fertilization dynamics.

Infertility, recognized by the World Health Organization (WHO) as a disease affecting the male or fe...

Proposing a machine learning-based model for predicting nonreassuring fetal heart.

The capacity to forecast nonreassuring fetal heart (NFH) is essential for minimizing perinatal compl...

Prediction of clinical risk factors in pregnancy using optimized neural network scheme.

Women should be aware of prenancy related health issues. A user-friendly model is developed in which...

Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images.

BACKGROUND: Homologous recombination deficiency (HRD) refers to the dysfunction of homologous recomb...

Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia.

Regulating inflammatory microglia presents a promising strategy for treating neurodegenerative and a...

Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device...

Accuracy of machine learning and traditional statistical models in the prediction of postpartum haemorrhage: a systematic review.

OBJECTIVES: To evaluate whether postpartum haemorrhage (PPH) can be predicted using both machine lea...

Enhancing Personalized Chemotherapy for Ovarian Cancer: Integrating Gene Expression Data with Machine Learning.

OBJECTIVE:  Ovarian cancer's complexity and heterogeneity pose significant challenges in treatment, ...

A deep ensemble learning approach for squamous cell classification in cervical cancer.

Cervical cancer, arising from the cells of the cervix, the lower segment of the uterus connected to ...

OnmiMHC: a machine learning solution for UCEC tumor vaccine development through enhanced peptide-MHC binding prediction.

The key roles of Major Histocompatibility Complex (MHC) Class I and II molecules in the immune syste...

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse event...

Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy.

This study was conducted to develop and validate a novel deep reinforcement learning (DRL) algorithm...

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