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【Mingli lecture 2022, Issue 16】4-7 Professor Tongxin Zhou : Spoiled for Choice? Personalized Recommendation for Healthcare Decisions

【Mingli lecture 2022, Issue 16】

Time: April 7 (Thursday) 10:15-11:30 am

Tencent conference number: [288 108 064]

Speaker: Professor Tongxin Zhou from Arizona State University, USA

Speaker Profile:

Tongxin Zhou is an Assistant Professor of Information Systems at Arizona State University's W. P. Carey School of Business. Current research focuses on healthcare analytics, using econometrics, machine learning, and statistical modeling tools to study a variety of healthcare-related topics, including the dynamics of healthcare behavior of patients and physicians on online platforms and artificial intelligence in healthcare applications in health care. Her works have been published in top journals such as Management Science, Information Systems Research, etc., and have been shortlisted for the 2018 INFORMS eBusiness Best Paper Competition, as well as the 2018 and 2020 CHITA (Conference on Health IT and Analytics) Best Student Paper Competition finalists. Member of INFORMS, Information Systems Society, Health Applications Society, Computing Society, and Association for Information Systems.

Introduction to the report:

The study follows a design science paradigm to develop a personalized recommendation framework to help individuals better engage in online medical interventions. Considering the main challenges of intervention adaptation and diversity in highly dynamic environments, we propose an innovative online learning framework that integrates deep contextual representations and a theory-guided diversity promotion scheme. By rigorously evaluating our method on a real dataset from an online weight loss community, after a series of experiments, we found strong evidence for the effectiveness of our proposed recommendation framework. Our research contributes to emerging research in prescriptive analytics and business intelligence applications. The proposed modeling framework incorporates several methodological novelties and has important practical implications for multiple stakeholders including online healthcare platforms, policymakers, and users.

(Organizer: Department of Management Engineering, Research and Academic Exchange Center)

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