Obstetrics & Gynecology

Pregnancy

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

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Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization.

Assisted reproductive technology is helping humans by addressing infertility using different medical...

Minimizing Image Quality Loss After Channel Count Reduction for Plane Wave Ultrasound via Deep Learning Inference.

High-frame-rate ultrasound imaging uses unfocused transmissions to insonify an entire imaging view f...

Predicting the level of anemia among Ethiopian pregnant women using homogeneous ensemble machine learning algorithm.

BACKGROUND: More than 115,000 maternal deaths and 591,000 prenatal deaths occurred in the world per ...

Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning.

Clinical guidelines recommend several risk factors to identify women in early pregnancy at high risk...

Automatic Segmentation of Periodontal Tissue Ultrasound Images with Artificial Intelligence: A Novel Method for Improving Dataset Quality.

UNLABELLED: This research aimed to evaluate Mask R-CNN and U-Net convolutional neural network models...

Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks.

In this work, we present a novel gaze-assisted natural language processing (NLP)-based video caption...

Application and Communication Optimization Technology of Unmanned Distribution Car under Deep Learning in Logistics Express of COVID-19.

This work aims to solve the problem that the daily necessities of urban residents cannot be delivere...

Research progress and hotspot of the artificial intelligence application in the ultrasound during 2011-2021: A bibliometric analysis.

Ultrasound, as a common clinical examination tool, inevitably has human errors due to the limitation...

Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study.

Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultr...

Prediction of placenta accreta spectrum by combining deep learning and radiomics using T2WI: a multicenter study.

PURPOSE: To achieve prenatal prediction of placenta accreta spectrum (PAS) by combining clinical mod...

Machine learning in project analytics: a data-driven framework and case study.

The analytic procedures incorporated to facilitate the delivery of projects are often referred to as...

Exploring the Application of BIM Technology in the Whole Process of Construction Cost Management with Computational Intelligence.

The construction industry is a labor-intensive industry in China. In recent years, as people's livin...

Development and validation of a machine-learning algorithm to predict the relevance of scientific articles within the field of teratology.

The Dutch Teratology Information Service Lareb counsels healthcare professionals and patients about ...

Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning.

Recently, super-resolution ultrasound imaging with ultrasound localization microscopy (ULM) has rece...

Use of Deep Learning to Detect the Maternal Heart Rate and False Signals on Fetal Heart Rate Recordings.

We have developed deep learning models for automatic identification of the maternal heart rate (MHR)...

Improvement of Patient Classification Using Feature Selection Applied to Bidirectional Axial Transmission.

Osteoporosis is still a worldwide problem, particularly due to associated fragility fractures. Patie...

Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy.

BACKGROUND: Accurate diagnosis of unexplained cervical lymphadenopathy (CLA) using medical images he...

C-Net: Cascaded convolutional neural network with global guidance and refinement residuals for breast ultrasound images segmentation.

BACKGROUND AND OBJECTIVE: Breast lesions segmentation is an important step of computer-aided diagnos...

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