Obstetrics & Gynecology

Pregnancy

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

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Prediction model development of late-onset preeclampsia using machine learning-based methods.

Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due to the ...

A Human Microrobot Interface Based on Acoustic Manipulation.

Micro/nanorobotic systems capable of targeted transporting and releasing hold considerable promise f...

Deeply-Supervised Networks With Threshold Loss for Cancer Detection in Automated Breast Ultrasound.

ABUS, or Automated breast ultrasound, is an innovative and promising method of screening for breast ...

Localizing B-Lines in Lung Ultrasonography by Weakly Supervised Deep Learning, In-Vivo Results.

Lung ultrasound (LUS) is nowadays gaining growing attention from both the clinical and technical wor...

Semiautomatic Fetal Intelligent Navigation Echocardiography Has the Potential to Aid Cardiac Evaluations Even in Less Experienced Hands.

OBJECTIVES: To investigate the interobserver and intraobserver variability and corresponding learnin...

Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs.

PURPOSE: In this paper, we propose to apply generative adversarial neural networks trained with a cy...

How and why should the radiologist look at the placenta?

This editorial comment refers to the article "Identification of suspicious invasive placentation bas...

Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis.

BACKGROUND: Multiple sclerosis (MS) is a chronic neurological disease occurring mostly in women of c...

Performance of machine learning software to classify breast lesions using BI-RADS radiomic features on ultrasound images.

BACKGROUND: The purpose of this work was to evaluate computable Breast Imaging Reporting and Data Sy...

Efficacy of Ultrasound-Guided Caudal Epidural Calcitonin for Patients with Failed Back Surgery Syndrome.

CONTEXT: Pain resulting from failed back surgery syndrome (FBSS) is generally resistant to physiothe...

Reaffirmation of the importance of follow-up ultrasound studies in patients with high D-dimers and clinical suspicion of vein thrombosis.

BACKGROUND: Venous thromboembolism is a common disease seen in the emergency department and a cause ...

Self-supervised learning for medical image analysis using image context restoration.

Machine learning, particularly deep learning has boosted medical image analysis over the past years....

Evaluation of machine learning methods with Fourier Transform features for classifying ovarian tumors based on ultrasound images.

INTRODUCTION: Ovarian tumors are the most common diagnostic challenge for gynecologists and ultrasou...

A Deep Learning Framework for Single-Sided Sound Speed Inversion in Medical Ultrasound.

OBJECTIVE: Ultrasound elastography is gaining traction as an accessible and useful diagnostic tool f...

Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches.

Textile industry wastewaters, which cause serious problems in the environment and human health, incl...

Learning the implicit strain reconstruction in ultrasound elastography using privileged information.

Quasi-static ultrasound elastography is an importance imaging technology to assess the conditions of...

Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images.

The goal of this work was to develop a method for accurate and robust automatic segmentation of the ...

Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning.

Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastase...

Classification of Carotid Artery Intima Media Thickness Ultrasound Images with Deep Learning.

Cerebrovascular accident due to carotid artery disease is the most common cause of death in develope...

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