Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical le...
Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection
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England: British Medical Journal Publishing Group
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Language
English
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England: British Medical Journal Publishing Group
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IntroductionCongenital anomalies are the most encountered cause of fetal death, infant mortality and morbidity. 7.9 million infants are born with congenital anomalies yearly. Early detection of congenital anomalies facilitates life-saving treatments and stops the progression of disabilities. Congenital anomalies can be diagnosed prenatally through...
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Full title
Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection
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TN_cdi_doaj_primary_oai_doaj_org_article_4209432668564070b47b9e0dddecafcc
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4209432668564070b47b9e0dddecafcc
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ISSN
2044-6055
E-ISSN
2044-6055
DOI
10.1136/bmjopen-2023-077366
