Big Data for Reproductive Health (BD4RH Year 2)

Big Data for Reproductive Health (BD4RH Year 2)

2019

Dennis Harrsch, Jr. ( Computer Science ), Elizabeth Loschiavo ( Sociology ), and Zhixue (Mary) Wang ( Computer Science, Statistics ) spent ten weeks improving upon the team’s web platform that allows users to examine contraceptive use in low and middle income (LMIC) countries collected by the Demographic and Health Survey (DHS) contraceptive calendar. The team improved load times, data visualization latency, and increased the number of country surveys available in the platform from 3 to 55. The team also created a new app that allows users to explore the results of machine learning using this big data set.

This project will continue into the academic year via Bass Connections where student teams will refine the machine learning model results and explore the question of whether and how policymakers can use these tools to improve family planning in LMIC settings.

 

Click here to view the Executive Summary

 

Faculty Lead: Megan Huchko

Project Manager: Amy Finnegan

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Mathematics

Related People

Computer Science, Statistics

Sociology

Computer Science