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Prenatal Diagnosis

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Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potential to quantify the MRI features of PAS.

Use of artificial intelligence and deep learning in fetal ultrasound imaging.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Deep learning is considered the leading artificial intelligence tool in image analysis in general. Deep-learning algorithms excel at image recognition, which makes them valuable in medical imaging. Obstetric ultrasound has become the gold standard im...

Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVE: Prenatal diagnosis of a rare disease on ultrasound relies on a physician's ability to remember an intractable amount of knowledge. We developed a real-time decision support system (DSS) that suggests, at each step of the examination, the n...

Development and validation of an artificial intelligence assisted prenatal ultrasonography screening system for trainees.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: Fetal anomaly screening via ultrasonography, which involves capturing and interpreting standard views, is highly challenging for inexperienced operators. We aimed to develop and validate a prenatal-screening artificial intelligence system ...

Deep-learning model for prenatal congenital heart disease screening generalizes to community setting and outperforms clinical detection.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVES: Despite nearly universal prenatal ultrasound screening programs, congenital heart defects (CHD) are still missed, which may result in severe morbidity or even death. Deep machine learning (DL) can automate image recognition from ultrasoun...

The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening.

Talanta
To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease (FCHD), establish the FCHD diagnostic models, and assess the performance of these models, we recruited two batches of pregnant women. By metabolomics...

Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.

Scientific reports
Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularly in the field of medical imaging. In this study, we investigated the application of deep learning models in early detection of fetal kidney anomalies...

Artificial intelligence-based diagnosis in fetal pathology using external ear shapes.

Prenatal diagnosis
OBJECTIVE: Here we trained an automatic phenotype assessment tool to recognize syndromic ears in two syndromes in fetuses-=CHARGE and Mandibulo-Facial Dysostosis Guion Almeida type (MFDGA)-versus controls.