Obstetrics & Gynecology

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

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Latent representation learning for classification of the Doppler ultrasound images.

The classification of Doppler ultrasound images plays an important role in the diagnosis of pregnanc...

Development of a machine learning model to classify polycystic ovarian syndrome.

BackgroundOne of the main causes of infertility among women nowadays is Polycystic Ovarian Syndrome,...

A unified deep-learning framework for enhanced patient-specific quality assurance of intensity-modulated radiation therapy plans.

BACKGROUND: Modern radiation therapy techniques, such as intensity-modulated radiation therapy (IMRT...

Trajectory of breastfeeding among Chinese women and risk prediction models based on machine learning: a cohort study.

BACKGROUND: Breastfeeding is the optimal source of nutrition for infants and young children, essenti...

A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after ...

Automated assessment of endometrial receptivity for screening recurrent pregnancy loss risk using deep learning-enhanced ultrasound and clinical data.

BACKGROUND: Recurrent pregnancy loss (RPL) poses significant challenges in clinical management due t...

Automatic Pavlov ratio measurement method based on spinal landmarks identification by a deep-learning model.

BACKGROUND: Cervical canal stenosis is one of the important pathogenic factors of cervical spondylos...

Artificial intelligence and sexual reproductive health and rights: a technological leap towards achieving sustainable development goal target 3.7.

Target 3.7 of the Sustainable Development Goals (SDGs) aims for universal access to sexual and repro...

AI and Technology Enabled Clinical Workflow Redesign.

The rapid evolution of digital health technologies has significantly transformed health care deliver...

Predicting preterm birth using electronic medical records from multiple prenatal visits.

This study aimed to predict preterm birth in nulliparous women using machine learning and easily acc...

NMF typing and machine learning algorithm-based exploration of preeclampsia-related mechanisms on ferroptosis signature genes.

BACKGROUND: Globally, pre-eclampsia (PE) poses a major threat to the health and survival of pregnant...

Pre-trained artificial intelligence language model represents pragmatic language variability central to autism and genetically related phenotypes.

Many individuals with autism experience challenges using language in social contexts (i.e., pragmati...

Machine learning analysis of sex and menopausal differences in the gut microbiome in the HELIUS study.

Sex differences in the gut microbiome have been examined previously, but results are inconsistent, o...

Enhancing decision-making in tubal ectopic pregnancy using a machine learning approach to expectant management: a clinical article.

OBJECTIVE: To refine decision-making regarding expectant management for ectopic pregnancy (EP) using...

Cubosomes as Delivery System to Repositioning Nitrofurantoin in Breast Cancer Management.

PURPOSE: Nitrofurantoin (NITRO), a long-standing antibiotic to treat urinary tract infections, is ac...

Actuation-Mediated Compression of a Mechanoresponsive Hydrogel by Soft Robotics to Control Release of Therapeutic Proteins.

Therapeutic proteins, the fastest growing class of pharmaceuticals, are subject to rapid proteolytic...

Leveraging machine learning models for anemia severity detection among pregnant women following ANC: Ethiopian context.

BACKGROUND: Anemia during pregnancy is a significant public health concern, particularly in resource...

Pixels to precision: Neuroradiology's leap into 3D printing for personalized medicine.

The realm of precision medicine, particularly its application within various sectors, shines notably...

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