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Ongoing Study Identifies Pregnant Women Whose Fetuses Are Most Likely to Develop Heart Problems Tied to Lupus and Other Autoimmune Diseases

Donald Wayne Moon

Fetal Heart Defect Detection Improved by Using Machine Learning

Researchers identify new way to improve the diagnosis of fetal heart defects

UC San Francisco researchers have found a way to double doctors' accuracy in detecting the vast majority of complex fetal heart defects in utero - when interventions could either correct them or greatly improve a child's chance of survival - by combining routine ultrasound imaging with machine-learning computer tools.

UCSF improves fetal heart defect detection using machine learning

UC San Francisco researchers have found a way to double doctors accuracy in detecting the vast majority of complex fetal heart defects in utero - when interventions could either correct them or greatly improve a child s chance of survival - by combining routine ultrasound imaging with machine-learning computer tools.

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