How Data Science Predicts and Reduces Adverse Birth Outcomes

           Tweet Previous post Tags: chil, DSSG, Healthcare, Jim O’ Donoghue Here we look at project from Chicago University’s Data Science for Social Good (DSSG) Program on Predicting and Reducing Adverse Birth Outcomes. By By Jim O’ Donoghue, @J_ODonoghue. In this post we examine DSSG project on Predicting and Reducing Adverse Birth Outcomes. Worldwide mortality rates of children under five have dropped 53% between 1990 and 2015 but have missed the 66% target. 16,000 children under five still die every day. Although this project is US based, where there are less than 25 deaths for every 1000 live births it is a framework that could be expanded to Sub-Saharan Africa where help is needed most and the mortality rate is over 4 times greater. An adverse birth is…


Link to Full Article: How Data Science Predicts and Reduces Adverse Birth Outcomes

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