Dr. William Hsu's research aims to uncover predictive patterns from longitudinal clinical, imaging and genomic data to improve clinical decision making. His work has primarily contributed to four areas:
- Adapting and validating novel decision models to discover optimal strategies for individual patients;
- Formalizing literature for treatment selection and experiment planning;
- Improving the generalizability of predictive models; and
- Developing translational applications towards precision medicine.
These developments are being practically implemented in lung, prostate, brain and breast cancer.
Rios Piedra EA, Taira RK, El-Saden S, Ellingson BM, Bui AAT, Hsu W. Assessing Variability in Brain Tumor Segmentation to Improve Volumetric Accuracy and Characterization of Change. IEEE EMBS Int Conf Biomed Health Inform. 2016 Feb;2016:380-383. doi: 10.1109/BHI.2016.7455914. Epub 2016 Apr 21.
Katrib A, Hsu W, Bui A, Xing Y. "RADIOTRANSCRIPTOMICS": A synergy of imaging and transcriptomics in clinical assessment. Quant Biol. 2016 Mar;4(1):1-12. doi: 10.1007/s40484-016-0061-6. Epub 2016 Mar 4.
Hsu W, El-Saden S, Taira RK. Medical Imaging Informatics. Adv Exp Med Biol. 2016;939:167-224. Review.
Song L, Hsu W, Xu J, van der Schaar M. Using Contextual Learning to Improve Diagnostic Accuracy: Application in Breast Cancer Screening. IEEE J Biomed Health Inform. 2016 May;20(3):902-914. doi: 10.1109/JBHI.2015.2414934. Epub 2015 Mar 20.
Hsu W, Han SX, Arnold CW, Bui AA, Enzmann DR. A data-driven approach for quality assessment of radiologic interpretations. J Am Med Inform Assoc. 2016 Apr;23(e1):e152-6. doi: 10.1093/jamia/ocv161. Epub 2015 Nov 25.