Graham School News

Medical Analytics Projects With Machine Learning Receive Best-in-Showcase Awards at Two-Session Master of Science in Analytics 2017 Capstone Showcase Event

Analytics students present their capstone project

On Saturday, December 2, the Masters of Science in Analytics (MScA) program held one of its largest Capstone Showcase events yet, a felicitous occasion requiring presentations to take place in two sessions in two different rooms and calling for two teams to be granted the $5,000 Best-in-Showcase prizes, awards to be spent in the upcoming year while attending an analytics-related conference.

“It was a great pleasure to see so many successful presentations at the MScA Capstone Showcase event on Saturday,” said Sema Barlas, MScA program director. “The presentations were excellent, the participation was good, and it was one of the largest Capstone Showcases yet. I would like to thank all the students and their supervisors for working so hard to achieve such a substantial outcome.”

MScA Capstone group who successfully completed a health analytics capstone project that helps detect hepatitis C

Noting the extremely tight competition and intense debate required by the two session’s juries in deciding the winners, Barlas announced that the Session One Best-in-Show award was earned by Hristina Hristova, Cindy Kartman, and Laura Olson, whose project “Early Detection of Hepatitis C Virus and Predicting Treatment Adherence Using Electronic Medical Records” demonstrated excellence in assuring data quality and model portability, as well as an impressive ability to identify their analytical model’s business impact. 

With faculty advisor Arnab Bose, managing director with Abzooba, the team used electronic medical records from the University of Chicago Medical Center to refine the screening algorithms for diagnosing patients infected with the hepatitis C virus. Using machine learning methods to conduct their research, their results could provide primary care providers with information to help personalize treatment programs.

MScA capstone group who successfully completed a health analytics project to identify unclaimed medical rebates

Receiving Best-in-Show for Session Two were Wendy Gao, Dongping Jing, and Xiaolei Sun, whose presentation entitled “Detecting Ineligible Medical Rebate Claims Using Machine Learning” demonstrated an advanced understanding of their problem as well as clear and actionable insights arrived at through their use of analytics. Advised by Yuri Balasanov, lecturer for both the UChicago MScA program and Financial Mathematics program, the team built a machine-learning model for detecting ineligible medical rebate claims.

Judging Session One were Shaddy Abado, staff data scientist with General Electric Digital and MScA lecturer, Michael Besedick, business consultant with Surgical Directions and MScA alum, and Joe DeCosmo, chief analytics officer for Enova International as well as MScA industry partner. For Session Two, the jury was comprised of Debtosh Banerjee, director at AVANT and MScA alum, Vinod Cheriyan, lead data scientist with Enova International and MScA industry partner, and Ming Long Lam, principal research statistician with the SAS Institute and MScA lecturer.

Four teams were also given honorable mentions for the professional quality of their presentations along with the clarity and insight they were able to bring the problems they analytically addressed. Members of these teams were: Neha Belthur, David Hsiao, Arka Khasnabis, and Rachel Mok for their project evaluating healthcare shoppers; Orest Alickolli, Hussam Almuayad, and Joseph Koizim for their project focused on restaurant menu optimization; Sachin Agrawal and Atul Goel for their project entitled “B2W- Product Design and Customer Segmentation”; and Minghao Bian, Ziyuan Li, Zhiyin Shi, and Jianghui Wen for their project assessing machine learning algorithms and libraries in big data applications.