{"id":244660,"date":"2019-05-05T17:50:00","date_gmt":"2019-05-05T21:50:00","guid":{"rendered":"https:\/\/dev.oviauser.com\/?p=244660"},"modified":"2019-05-05T17:50:00","modified_gmt":"2019-05-05T21:50:00","slug":"machine-learning-predicts-risk-of-preterm-delivery","status":"publish","type":"post","link":"https:\/\/www.oviahealth.com\/blog\/machine-learning-predicts-risk-of-preterm-delivery\/","title":{"rendered":"Machine learning predicts risk of preterm delivery"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Predicting the likelihood of delivery preterm using data collected from a pregnancy mobile app<\/h2>\n\n\n\n<h5 class=\"wp-block-heading\">Published: American College of Obstetricians and Gynecologists (ACOG)<\/h5>\n\n\n\n<h5 class=\"wp-block-heading\">Authors: Bradley, Danielle MS, MPH; Landau, Erin; Wolfberg, Adam MD, MPH; Baron, Alex PhD <\/h5>\n\n\n\n<p>Risk for preterm delivery is largely only identified among women with previous preterm deliveries or explicit risk factors, like insufficient cervix. But for the other group of seemingly low risk women who end up delivering preterm, there are very few proven methods for identifying risk in time to intervene.<\/p>\n\n\n\n<p>Ovia Health\u2019s data science team applied machine learning methodologies to determine our ability to detect the likelihood of delivering preterm. We were able to detect 41% of cases with 75% positive predictive value. The results of which were peer-reviewed and presented at the American College of Obstetricians and Gynecologists (ACOG) annual conference.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-white-color has-text-color has-background\" href=\"\" style=\"background-color:#f8a79b\" target=\"_blank\" rel=\"https:\/\/info.oviahealth.com\/care-continuity noopener\">Download the full study<\/a><\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">About Ovia Health<\/h3>\n\n\n\n<p>Ovia Health has helped over 14 million women and families. We offer a comprehensive maternity and family benefits solution from preconception and pregnancy through return-to-work and parenthood.&nbsp;<\/p>\n\n\n\n<p><strong>Ovia Health:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Engages women early, and sustains long term daily participation<\/li><li>Actively encourages partners to participate in the process<\/li><li>Includes predictive coaching and mobile alerts for identified health issues<\/li><li>Supports return-to-work with a proven approach<\/li><li>Boosts utilization across an employer\u2019s benefit ecosystem<\/li><li>Drives behavior change and reduces maternity costs<\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Predicting the likelihood of delivery preterm using data collected from a pregnancy mobile app Published: American College of Obstetricians and Gynecologists (ACOG) Authors: Bradley, Danielle MS, MPH; Landau, Erin; Wolfberg, Adam MD, MPH; Baron, Alex PhD Risk for preterm delivery is largely only identified among women with previous preterm deliveries or explicit risk factors, like [&hellip;]<\/p>\n","protected":false},"author":26,"featured_media":244661,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"ovia_blog_author":"","ovia_blog_author_image":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[3460,3472],"tags":[],"class_list":["post-244660","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-clinical","category-research-clinical"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - 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