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20212025
most citedScalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health

3 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2025

Beyond Listenership: AI-Predicted Interventions Drive Improvements in Maternal Health Behaviours

Arpan Dasgupta, Sarvesh Gharat, Neha Madhiwalla +3

Automated voice calls with health information are a proven method for disseminating maternal and child health information among beneficiaries and are deployed in several programs a…

cs.AI2025

Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Improved Message Delivery in Mobile Maternal Health

Arpan Dasgupta, Mizhaan Maniyar, Awadhesh Srivastava +7

Mobile health (mHealth) programs utilize automated voice messages to deliver health information, particularly targeting underserved communities, demonstrating the effectiveness of…

cs.CY2024

Improving Health Information Access in the World's Largest Maternal Mobile Health Program via Bandit Algorithms

Arshika Lalan, Shresth Verma, Paula Rodriguez Diaz +6

Harnessing the wide-spread availability of cell phones, many nonprofits have launched mobile health (mHealth) programs to deliver information via voice or text to beneficiaries in…

cs.HC2024★ 1 cited

Preliminary Study of the Impact of AI-Based Interventions on Health and Behavioral Outcomes in Maternal Health Programs

Arpan Dasgupta, Niclas Boehmer, Neha Madhiwalla +4

Automated voice calls are an effective method of delivering maternal and child health information to mothers in underserved communities. One method to fight dwindling listenership…

cs.LG2023

Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile Health Program: A Preliminary Investigation

Arshika Lalan, Shresth Verma, Kumar Madhu Sudan +4

Mobile health programs are becoming an increasingly popular medium for dissemination of health information among beneficiaries in less privileged communities. Kilkari is one of the…

cs.LG2022★ 3 cited

Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health

Kai Wang, Shresth Verma, Aditya Mate +5

This paper studies restless multi-armed bandit (RMAB) problems with unknown arm transition dynamics but with known correlated arm features. The goal is to learn a model to predict…

cs.LG2021

Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health

Aditya Mate, Lovish Madaan, Aparna Taneja +6

The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work t…

cs.LG2021

Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes

Siddharth Nishtala, Lovish Madaan, Aditya Mate +11

India has a maternal mortality ratio of 113 and child mortality ratio of 2830 per 100,000 live births. Lack of access to preventive care information is a major contributing factor…