题目: 医疗保健干预的个性化推荐

Spoiled for Choice? Personalized Recommendation for Healthcare Decisions: A Multi-Armed Bandit Approach

演讲人: 周彤昕助理教授， 亚利桑那州立大学商学院

时间: 2022年3月22日上午9:00-10:00

地点: 线上腾讯会议

会议号：466 236 547 会议密码：722500

讲座摘要:

Online healthcare platforms provide users with various intervention programs to help them promote personal wellness. Given the many choices available, individuals can often find it difficult to decide which intervention to select, especially when they lack the experience or knowledge to evaluate different options. This may discourage individuals’ continuous engagement in online health management. In this study, we are motivated to follow the design-science paradigm to develop a personalized recommendation framework to help individuals better engage in online healthcare interventions. Taking into account the major challenges in intervention adaptation and diversification in a highly dynamic environment, we propose a innovated online learning framework that synthesizes deep-learning-based feature engineering and a theory-guided diversity promotion scheme. We rigorously evaluate our approach on a real-world dataset on users’ intervention participation in an online weight-loss community. Through a series of experiments, we find strong evidence for the effectiveness of our proposed recommendation framework. Our study contributes to the emerging IS research on prescriptive analytics and the application of business intelligence. The proposed modeling framework contain various methodological novelties and have important practical implications for multiple stakeholders, including online healthcare platforms, policymakers, and users.

演讲嘉宾简介:

Tongxin Zhou is an Assistant Professor of Information Systems at the W. P. Carey School of Business, Arizona State University. Her current research focuses on healthcare analytics. In her research, she uses tools of econometrics, machine learning, and statistical modeling to study various healthcare-related topics, including patients’ and physicians’ healthcare behavior dynamics in online platforms and the application of AI in healthcare. Her works have been published in top-tier journals such as Management Science, Information Systems Research, and have been recognized as a finalist in 2018 INFORMS eBusiness Best Paper Competition and a finalist in 2018 and 2020 CHITA (Conference on Health IT and Analytics) Best Student Paper Competition.

She teaches the undergraduate upper-division course of CIS 325 (Programming for Business Analytics) and serves on various committees at the Information Systems department at ASU. She is a member of INFORMS, Information Systems Society, Health Applications Society, Computing Society, and Association for Information Systems.

Prior to joining the W. P. Carey School of Business, she earned a Ph.D. degree in Business Administration from the Michael G. Foster School of Business, University of Washington, a Bachelor’s degree in Mathematical Statistics from the School of Statistics and Management in Shanghai University of Finance and Economics in China.