Obstetrics & Gynecology

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

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Showing 1051-1071 of 2,437 articles
Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

Deep learning technology has been used in the medical field to produce devices for clinical practice...

Tafoxiparin, a novel drug candidate for cervical ripening and labor augmentation: results from 2 randomized, placebo-controlled studies.

BACKGROUND: Slow progression of labor is a common obstetrical problem with multiple associated compl...

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imagin...

Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT.

OBJECTIVES: To develop an artificial intelligence (AI) system for predicting cervical lymph node met...

Predicting preterm births from electrohysterogram recordings via deep learning.

About one in ten babies is born preterm, i.e., before completing 37 weeks of gestation, which can re...

Associating Peritoneal Metastasis With T2-Weighted MRI Images in Epithelial Ovarian Cancer Using Deep Learning and Radiomics: A Multicenter Study.

BACKGROUND: The preoperative diagnosis of peritoneal metastasis (PM) in epithelial ovarian cancer (E...

Real-Time Automatic Assisted Detection of Uterine Fibroid in Ultrasound Images Using a Deep Learning Detector.

OBJECTIVE: Uterine smooth muscle hyperplasia causes a tumor called a uterine fibroid. With an incide...

CervicoXNet: an automated cervicogram interpretation network.

Visual inspection with acetic acid (VIA) is a pre-cancerous screening program for low-middle-income ...

Growing pains: strategies for improving ergonomics in minimally invasive gynecologic surgery.

PURPOSE OF REVIEW: To evaluate factors contributing to the development of work-related musculoskelet...

A Deep Learning-Based System Trained for Gastrointestinal Stromal Tumor Screening Can Identify Multiple Types of Soft Tissue Tumors.

The accuracy and timeliness of the pathologic diagnosis of soft tissue tumors (STTs) critically affe...

Bubble-Based Microrobots with Rapid Circular Motions for Epithelial Pinning and Drug Delivery.

Remotely powered microrobots are proposed as next-generation vehicles for drug delivery. However, mo...

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis.

OBJECTIVE: Ovarian cancer is a significant health issue with lasting impacts on the community. Despi...

Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms.

Cervical cancer is the most common reproductive malignancy in the female reproductive system. The in...

Development and validation of a deep learning survival model for cervical adenocarcinoma patients.

BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for cervic...

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.

Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of ...

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies ...

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy.

. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the f...

Application of artificial intelligence centric workflows for evaluation of neuroradiology emergencies.

The goal of this study was to perform a pilot study to assess user-interface of radiologists with an...

Deep learning-based high-accuracy detection for lumbar and cervical degenerative disease on T2-weighted MR images.

PURPOSE: To develop and validate a deep learning (DL) model for detecting lumbar degenerative diseas...

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