首页|University of Pittsburgh Reports Findings in Machine Learning (Periconceptional dietary patterns and adverse pregnancy and birth outcomes)
University of Pittsburgh Reports Findings in Machine Learning (Periconceptional dietary patterns and adverse pregnancy and birth outcomes)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is the subject of a report. According to news originatingfrom Pittsburgh, Pennsylvania, by NewsRx correspondents, research stated, “The periconceptionalperiod is a critical window for the origins of adverse pregnancy and birth outcomes, yet little is knownabout the dietary patterns that promote perinatal health. We used machine learning methods to determinethe effect of periconceptional dietary patterns on the risk of preeclampsia, gestational diabetes, pretermbirth, small-for-gestational-age (SGA) birth, and a composite of these outcomes.”
PittsburghPennsylvaniaUnited StatesNorth and Central AmericaBeverageCyborgsEmerging TechnologiesFoodHealth and MedicineMachine LearningObstetricsPreeclampsiaPregnancy ComplicationsWomen’s Health
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