Obstetrics & Gynecology

Pregnancy

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

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Emerging Feature Extraction Techniques for Machine Learning-Based Classification of Carotid Artery Ultrasound Images.

Plaque deposits in the carotid artery are the major cause of stroke and atherosclerosis. Ultrasound ...

The feasibility to use artificial intelligence to aid detecting focal liver lesions in real-time ultrasound: a preliminary study based on videos.

Despite the wide availability of ultrasound machines for hepatocellular carcinoma surveillance, an i...

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients.

In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promisi...

Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy.

Nucleated red blood cells (NRBCs) as a type of rare cell present in an adult's peripheral blood is a...

Deep learning-based plane pose regression in obstetric ultrasound.

PURPOSE: In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dime...

Computer Vision-Based Medical Cloud Data System for Back Muscle Image Detection.

The fast development of image recognition and information technology has influenced people's life an...

Using DeepLab v3 + -based semantic segmentation to evaluate platelet activation.

This research used DeepLab v3 + -based semantic segmentation to automatically evaluate the platelet ...

Investigating Shift Variance of Convolutional Neural Networks in Ultrasound Image Segmentation.

While accuracy is an evident criterion for ultrasound image segmentation, output consistency across ...

Neural Network Kalman Filtering for 3-D Object Tracking From Linear Array Ultrasound Data.

Many interventional surgical procedures rely on medical imaging to visualize and track instruments. ...

Deep Learning-Based Classification of Reduced Lung Ultrasound Data From COVID-19 Patients.

The application of lung ultrasound (LUS) imaging for the diagnosis of lung diseases has recently cap...

Deep-Learning Based Adaptive Ultrasound Imaging From Sub-Nyquist Channel Data.

Traditional beamforming of medical ultrasound images relies on sampling rates significantly higher t...

A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography.

Non-invasive foetal electrocardiography (NI-FECG) has become an important prenatal monitoring method...

Clinical target segmentation using a novel deep neural network: double attention Res-U-Net.

We introduced Double Attention Res-U-Net architecture to address medical image segmentation problem ...

Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda.

Machine Learning (ML) has been widely used in predicting the mode of childbirth and assessing the po...

Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions.

The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscop...

Robotic CME in obese patients: advantage of robotic ultrasound scan for vascular dissection.

Complete mesocolic excision (CME) in right-sided colon cancers appears to confer oncological benefit...

Automatic measurement of fetal head circumference using a novel GCN-assisted deep convolutional network.

The growth of the fetus can be effectively monitored by measuring the fetal head circumference (HC) ...

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