AIMC Topic: Nervous System Malformations
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A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.
Metabolomics : Official journal of the Metabolomic Society
May 25, 2018
BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more a...
Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Mar 1, 2022
OBJECTIVES: To develop and validate an artificial intelligence system, the Prenatal ultrasound diagnosis Artificial Intelligence Conduct System (PAICS), to detect different patterns of fetal intracranial abnormality in standard sonographic reference ...
Brain views that benefit from three-dimensional ultrasound.
Current opinion in obstetrics & gynecology
Apr 1, 2021
PURPOSE OF REVIEW: Fetal central nervous system malformations are among the most common congenital anomalies. Whereas simple axial views are sufficient for basic fetal brain examination, other important views are essential for a more detailed examina...
Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Oct 1, 2020
OBJECTIVES: To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.
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