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William Hsu, PhD

Associate Professor of Radiology
Specialty
Medical Imaging Informatics
Contact Information
(310) 794-3536

Office Address:
924 Westwood Blvd, Suite 420
Los Angeles, CA 90024
Email: whsu@mednet.ucla.edu
Website: https://mii.ucla.edu/people/william-hsu-phd

William Hsu is an Associate Professor in the Department of Radiological Sciences and a member of the Medical Imaging & Informatics group. He received his Ph.D. in Biomedical Engineering with an emphasis in Medical Imaging Informatics from the University of California, Los Angeles in 2009 and a BS degree in Biomedical Engineering from the Johns Hopkins University in 2004. His research interests include data integration, predictive modeling, population health management, and imaging informatics. He is an active member of the American Medical Informatics Association, serving on the Working Group Steering Committee and as a leader in the Biomedical Imaging Informatics Working Group.

Research Interests

The accelerated pace by which biomedical big data is being generated in the healthcare enterprise holds enormous promise in developing individualized diagnostic and therapeutic strategies towards precision medicine. My research aims to improve the effectiveness, delivery, and utility of diagnostic imaging services by harnessing data that are generated and captured as part of routine clinical care. My research contributions have been focused in four areas:

  1. adapting and validating novel decision models and uncertainty analysis to discover optimal strategies for individual patients;
  2. formalizing literature for treatment selection and experiment planning;
  3. improving the generalizability of predictive models; and
  4. developing translational applications that assist clinical and translational researchers with interpreting available evidence for precision medicine.

These developments are being practically implemented in a variety of clinical areas, spanning early detection, diagnosis, and treatment.

Publications

Find recent publications on Google Scholar, PubMed, or ORCID profile.

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