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Multi-Group Reinforcement Learning for Maternal Health in Childbirth
Barbara Engelhardt · Promise Ekpo

When considering off-policy reinforcement learning methods for treatment policies in healthcare data, it is generally the case that the patient population is diverse and has different chronic conditions that we would like to take into account when identifying optimal treatment policies. In this work, we use multi-group Gaussian process regression models in a fitted Q-iteration framework to allow us to model these different patient subgroups and adapt the optimal policies to each subgroup while estimating these function across the entire patient population. We apply our multi-group reinforcement learning (MGRL) framework to the problem of optimal treatment policies for women in childbirth with pre-existing conditions and across ethnicities to show the performance against other state-of-the-art methods

Author Information

Barbara Engelhardt (Princeton University)
Promise Ekpo (Princeton University)

Promise Ekpo Osaine is a Princeton University Fall 2021 First year PhD Student at the Computer Science department where her research interest will focus on the application of Machine learning in Healthcare especially in the reduction of maternal and infant mortality.   A first-class (Summa Cum Laude) graduate of the Department of Computer Engineering, Class of 2020, University of Benin, Promise was the best graduating student of her department (CGPA: 4.75/5.00). She holds several awards such as Shell Undergraduate Scholarship 2016, NNPC Quiz (SPE Conference, 2018), Huawei and Glo Students Award for Academic Excellence 2019, and Michael Taiwo Scholarship 2020.   Promise was an intern with Shell where she developed technical skills in SQL, Python, and data management applications such as EP Catalogue, SharePoint, and ASSAI. She was involved in the Shell Eco-Marathon Monitoring Global project, where she did sentiment analysis and reporting. She has also worked with Union Bank as a data engineer where she did Extract, Transform, and Load processing using SQL Server Management tools and Visual Studio Code.   At the University of Benin, she held leadership roles such as; Secretary-General of Computer Engineering Association, Secretary-General of Engineering Final year committee, Academic coordinator Of Gospel pillars Campus fellowship, University Coordinator of the U-Genius Club for student academic outreach and free mentorship.   Promise owns a mentorship platform aimed at improving the educational opportunities of students and is the convener of the “Get an Undergraduate a scholarship”, project She plays piano for community church as well as campus fellowship.

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