Obstetrics & Gynecology

Pregnancy

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

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Deep visual nerve tracking in ultrasound images.

Ultrasound-guided regional anesthesia (UGRA) becomes a standard procedure in surgical operations and...

Automatic evaluation of fetal head biometry from ultrasound images using machine learning.

OBJECTIVE: Ultrasound-based fetal biometric measurements, such as head circumference (HC) and bipari...

Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function.

Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the bio...

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises hea...

DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in .

Seeing is believing. The direct observation of GFP-Atg8 vacuolar delivery under confocal microscopy ...

Application of Deep Learning in Quantitative Analysis of 2-Dimensional Ultrasound Imaging of Nonalcoholic Fatty Liver Disease.

OBJECTIVES: To verify the value of deep learning in diagnosing nonalcoholic fatty liver disease (NAF...

Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images.

PURPOSE: Quantification of carotid plaques has been shown to be important for assessing as well as m...

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.

MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development...

A Mechatronic Platform for Computer Aided Detection of Nodules in Anatomopathological Analyses via Stiffness and Ultrasound Measurements.

This study presents a platform for ex-vivo detection of cancer nodules, addressing automation of med...

Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net.

PURPOSE: Transrectal ultrasound (TRUS) is a versatile and real-time imaging modality that is commonl...

Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa.

PURPOSE: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis...

The significance of artificial intelligence in drug delivery system design.

Over the last decade, increasing interest has been attracted towards the application of artificial i...

Prediction of coronary thin-cap fibroatheroma by intravascular ultrasound-based machine learning.

BACKGROUND AND AIMS: Although grayscale intravascular ultrasound (IVUS) is commonly used for assessi...

Use of artificial intelligence (AI) in the interpretation of intrapartum fetal heart rate (FHR) tracings: a systematic review and meta-analysis.

OBJECTIVES: To determine the degree of inter-rater reliability (IRR) between human and artificial in...

Artificial Neural Network Analysis of Spontaneous Preterm Labor and Birth and Its Major Determinants.

BACKGROUND: Little research based on the artificial neural network (ANN) is done on preterm birth (s...

Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging.

Detecting acoustic shadows in ultrasound images is important in many clinical and engineering applic...

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound.

Automatic prostate segmentation in transrectal ultrasound (TRUS) images is of essential importance f...

Image Quality Improvement of Hand-Held Ultrasound Devices With a Two-Stage Generative Adversarial Network.

As a widely used imaging modality in the medical field, ultrasound has been applied in community med...

Automatic localization of anatomical regions in medical ultrasound images of rheumatoid arthritis using deep learning.

The pace of population aging is growing faster worldwide. The quality of life of the aging populatio...

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