Obstetrics & Gynecology

Pregnancy

Latest AI and machine learning research in pregnancy for healthcare professionals.

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Showing 673-693 of 3,236 articles
Deep Learning and Automatic Differentiation of Pancreatic Lesions in Endoscopic Ultrasound: A Transatlantic Study.

INTRODUCTION: Endoscopic ultrasound (EUS) allows for characterization and biopsy of pancreatic lesio...

ACL-DUNet: A tumor segmentation method based on multiple attention and densely connected breast ultrasound images.

Breast cancer is the most common cancer in women. Breast masses are one of the distinctive signs for...

Machine Learning Differentiates Between Benign and Malignant Parotid Tumors With Contrast-Enhanced Ultrasound Features.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) is frequently used to distinguish benign parotid tum...

Deep Learning Approaches for the Assessment of Germinal Matrix Hemorrhage Using Neonatal Head Ultrasound.

Germinal matrix hemorrhage (GMH) is a critical condition affecting premature infants, commonly diagn...

Development and validation of preeclampsia predictive models using key genes from bioinformatics and machine learning approaches.

BACKGROUND: Preeclampsia (PE) poses significant diagnostic and therapeutic challenges. This study ai...

Enhancing patient understanding in obstetrics: the role of generative AI in simplifying informed consent for labor induction with oxytocin.

Informed consent is a cornerstone of ethical medical practice, particularly in obstetrics where proc...

Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape.

BACKGROUND: The WHO's recommendations on antenatal care underscore the need for ultrasound assessmen...

Large language models to facilitate pregnancy prediction after in vitro fertilization.

We evaluated the efficacy of large language models (LLMs), specifically, generative pre-trained tran...

Optimizing lipid nanoparticles for fetal gene delivery in vitro, ex vivo, and aided with machine learning.

There is a clinical need to develop lipid nanoparticles (LNPs) to deliver congenital therapies to th...

Fetal Face: Enhancing 3D Ultrasound Imaging by Postprocessing With AI Applications: Myth, Reality, or Legal Concerns?

The use of artificial intelligence (AI) platforms is revolutionizing the performance in managing met...

Artificial intelligence in obstetric anaesthesiology - the future of patient care?

The use of artificial intelligence (AI) in obstetric anaesthesiology shows great potential in enhanc...

The Digital Transformation in Health: How AI Can Improve the Performance of Health Systems.

Mobile health has the potential to revolutionize health care delivery and patient engagement. In thi...

Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease.

We developed a multimodal ultrasound (US) deep learning (DL) fusion model to automatically classify ...

Machine learning models of cerebral oxygenation (rcSO) for brain injury detection in neonates with hypoxic-ischaemic encephalopathy.

The present study was designed to test the potential utility of regional cerebral oxygen saturation ...

Ultrasound for breast cancer detection: A bibliometric analysis of global trends between 2004 and 2024.

With the advancement of computer technology and imaging equipment, ultrasound has emerged as a cruci...

Artificial intelligence-driven predictive framework for early detection of still birth.

Predictive modeling is becoming increasingly popular in the context of early disease detection. The ...

Ultrasound-based artificial intelligence model for prediction of Ki-67 proliferation index in soft tissue tumors.

RATIONALE AND OBJECTIVES: To investigate the value of deep learning (DL) combined with radiomics and...

[AI-supported decision-making in obstetrics - a feasibility study on the medical accuracy and reliability of ChatGPT].

The aim of this study is to investigate the feasibility of artificial intelligence in the interpreta...

AI driven interpretable deep learning based fetal health classification.

In this study, a deep learning model is proposed for the classification of fetal health into 3 categ...

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