Latest AI and machine learning research in pregnancy for healthcare professionals.
BACKGROUND: The prevalence of nonalcoholic fatty liver disease is increasing over time worldwide, with similar trends to those of diabetes and obesity. A liver biopsy, the gold standard of diagnosis, is not favored due to its invasiveness. Meanwhile, noninvasive evaluation methods of fatty liver are still either very expensive or demonstrate poor diagnostic performances, thus, limiting their appli...
PURPOSE: To develop and assess a deep learning system that automatically detects angle closure and quantitatively measures angle parameters from ultrasound biomicroscopy (UBM) images using a deep learning algorithm.
Low specificity and operator dependency are the main problems of breast ultrasound (US) screening. We investigated the added value of deep learning-ba...
PURPOSE: The purpose of this study was to develop a convolutional neural network (CNN) for automated localization of the scleral spur in ultrasound bi...
The purpose of this study was to explore whether the Nomogram, which was constructed by combining the Deep learning and Radiomic features of T2-weight...
Over the past half-century, ultrasound imaging has become a key technology for assessing an ever-widening range of medical conditions at all stages of...
Fetal weight is an important index to judge fetal development and ensure the safety of pregnant women. However, fetal weight cannot be directly measur...
In the current pandemic, lung ultrasound (LUS) played a useful role in evaluating patients affected by COVID-19. However, LUS remains limited to the v...
PURPOSE OF REVIEW: Fetal central nervous system malformations are among the most common congenital anomalies. Whereas simple axial views are sufficien...
Swimming biohybrid microsized robots (e.g., bacteria- or sperm-driven microrobots) with self-propelling and navigating capabilities have become an exc...
High-precision delivery of microrobots at the whole-body scale is of considerable importance for efforts toward targeted therapeutic intervention. How...
CONTEXT: Accurate methods for early gestational diabetes mellitus (GDM) (during the first trimester of pregnancy) prediction in Chinese and other popu...
BACKGROUND: Cardiotocography is a common method of electronic fetal monitoring (EFM) for fetal well-being. Data-driven analyses have shown potential f...
The aim of this work was o construct a score issued from a machine learning system with self-improvement capacity able to predict the fate of an ART e...
OBJECTIVES: To develop and test the performance of computerized ultrasound image analysis using deep neural networks (DNNs) in discriminating between ...
To evaluate and holistically treat the mental health sequelae and potential psychiatric comorbidities associated with obstetric and gynaecological con...
OBJECTIVE: We aim to present a case of a 43-year-old patient dia-gnosed with cervical adenocarcinoma in the 15th week of pregnancy, who underwent robo...
In order to improve the transfection efficiency of gene vectors and monitor the effect of gene therapy, this study prepared a drug delivery vector wit...
Hematopoietic stem and progenitor cells (HSPCs) develop in distinct waves at various anatomical sites during embryonic development. The in vitro diffe...
In many parts of Eastern India that have a very high prevalence of rural poverty and food insecurity, the prevailing rice establishment practice of ''...