Tata Institute of Fundamental Research

Using AI to assist in improving maternal and child health outcomes in underserved communities in India

Vigyan Vidushi
Speaker: Aparna Taneja (Google Research India)
Organiser: Mrinal Kumar, Ramprasad Saptharishi
Date: Thursday, 25 Jul 2024, 17:00 to 18:00
Venue: AG-66

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Abstract: 
The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This project assists non-profits that employ automated messaging programs to deliver timely preventive care information to beneficiaries (new and expecting mothers) during pregnancy and after delivery. Unfortunately, a key challenge in such information delivery programs is that a significant fraction of beneficiaries drop out of the program. Yet, non-profits often have limited health-worker resources (time) to place crucial service calls for live interaction with beneficiaries to prevent such engagement drops. To assist non-profits in optimizing this limited resource, we developed a Restless Multi-Armed Bandits (RMABs) system. The RMAB system was evaluated in collaboration with an NGO via a real-world service quality improvement study and showed a 30% reduction in engagement drops. This model was eventually deployed by the NGO and has served over 350K women so far. These encouraging results have led to a new collaboration with the Kilkari program, the largest maternal mHealth program in the world. And we hope to see similar improvements in engagement with the use of our AI model.
 
Short Bio:

Aparna is a researcher at the Multi Agents Systems for Social Impact team in Google Research India. She received her PhD in Computer Science at ETH Zurich under the supervision of Prof. Marc Pollefeys. She then pursued a postdoc at Disney Research Zurich. She collaborates with several NGO’s and academic partners in the fields of public health and conservation and her primary focus is collaboration with ARMMAN, an NGO focused on improving maternal and child health outcomes in underserved communities in India.