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NICHD Decoding Maternal Morbidity Data Challenge Winner’s Webinar

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Air date: Wednesday, March 16, 2022, 2:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 147 (6 Live, 141 On-demand)
Category: Special
Runtime: 01:28:31
Description: In 2021, NICHD launched the Decoding Maternal Morbidity Data Challenge to help advance research on maternal health and promote healthy pregnancies. The goal of the challenge was to devise new ways of analyzing data from NICHD’s Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b) to identify factors that impact maternal morbidity and severe maternal morbidity so that clinicians can more quickly and accurately identify and treat pregnancy-related conditions and prevent severe illness or death for a pregnant person.

Twelve prizes totaling $400,000 were awarded to seven teams/individuals. This webinar will bring together the winners to present their solutions.
NLM Title: NICHD decoding maternal morbidity data challenge winner's webinar / NICHD, NIH.
Author: National Institutes of Health (U.S.),
Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.),
Publisher:
Abstract: (CIT): In 2021, NICHD launched the Decoding Maternal Morbidity Data Challenge to help advance research on maternal health and promote healthy pregnancies. The goal of the challenge was to devise new ways of analyzing data from NICHD"s Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b) to identify factors that impact maternal morbidity and severe maternal morbidity so that clinicians can more quickly and accurately identify and treat pregnancy-related conditions and prevent severe illness or death for a pregnant person. Twelve prizes totaling $400,000 were awarded to seven teams/individuals. This webinar will bring together the winners to present their solutions.
Subjects: Data Analysis
Maternal Mortality
Pregnancy Complications--prevention & control
United States
Publication Types: Webcast
 
NLM Classification: WA 900 AA1
NLM ID: 9918384670106676
CIT Live ID: 45018
Permanent link: https://videocast.nih.gov/watch=45018