Research Interests

I am primarily interested in developing innovative data mining and machine learning solutions for challenging healthcare and biological problems. Improving patient health and quality of life is one of the primary motivators that stimulates my work.

Health 2.0 is definitely a buzzword but it isn't an empty one. I firmly believe that the future of healthcare is online. The possibility of online health records together with Web 2.0 staples like collective information sharing and social networking will result in the increased availability of relevant knowledge for patient health promotion leading to better educated patients who are healthier and happier. Hence, this is one of the areas that I am thoroughly interested in working on.

Rising healthcare costs. A common topic of discussion for many and rightly so. The growth rate in health expenditures is outpacing that of the gross domestic product, not only in the US but also across the globe, making it a critical economic and healthcare issue. One of the ways to reduce costs is through the identification of high-risk, high-cost patients who account for a large percentage of the healthcare expenditures. The proactive identification of such patients through predictive risk modeling allows for targeted health promotion programs that can improve their health and reduce direct costs as well as indirect costs to employers due to loss of productivity.

Publications

Sai T. Moturu, William G. Johnson, and Huan Liu. "Predictive Risk Modeling for Forecasting High-Cost Patients: A Real-World Application Using Medicaid Data", International Journal of Biomedical Engineering and Technology, Special Issue on Warehousing and Mining Complex Data: Applications to Biology, Medicine, Behavior, Health and Environment, forthcoming.

Sai T. Moturu, Huan Liu, and William G. Johnson. "Healthcare Risk Modeling for Medicaid Patients: The Impact of Sampling on the Prediction of High-Cost Patients", International Conference on Health Informatics (HEALTHINF 2008), Best Student Paper Award, Madeira, Portugal, January 28-31, 2008.

Sai T. Moturu, William G. Johnson, and Huan Liu. "Predicting Future High-Cost Patients: A Real-World Risk Modeling Application”, IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2007), San Jose, CA, Nov 2-4, 2007.

Sai Moturu, Lance Parsons, Zheng Zhao, and Huan Liu. "Integrative Data Analysis for Biological Discovery", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Idea Group, Inc. forthcoming.

E. G. Rajan, K. Kishore, Randhir Korlapati, Naveen Shankpal, Md. Riyazuddin and Sai Thejasvee Moturu. "On the Notion of Rapid Transform and Its Uses in Pattern Recognition", International Signal Processing Conference, Dallas, TX, Mar 31– Apr 3, 2003.

Posters

Christian Beaudry, Michael E. Berens, Tarek El Doker, Anna M. Joy, Lina J. Karam, Zoe Lacroix, Jad A. Lutfi, Sai Moturu, Rosemary A. Renaut, Ian J. Rich, “Automated Characterization of Cellular Migration Phenomena”, 4th IEEE International Computer Society Computational Systems Bioinformatics Conference (CSB) 2005.

Carol Baldwin, Norma Valenzuela, Bernadette Melnyk, Ellen Fineout-Overholt, Sai Moturu, Ma C. Cometto, Genoveva E. Avila, "Educational Needs of Nurses for Evidence-Based Practice in the Pan Americas", IX Conferencia Iberoamericana en Educación en Enfermería I Encuentro Latinoamerica Europa 2007.

Carol M. Baldwin, Bernadette Melnyk, Ellen Fineout-Overholt, Norma A. Valenzuela, Sai Moturu, "Comparison of EBP Learning Needs of U.S. and Pan American Nurses", 9th Annual Evidence-Based Practice Conference 2008.

Advisors

Dr Huan Liu, Associate Professor
Department of Computer Science and Engineering
Arizona State University

Dr William Johnson, Professor
Department of Biomedical Informatics
Director, Center for Health Information and Research
Arizona State University