William Hsu, PhD

Associate Professor
  • Department of Radiological Sciences
Affiliate Faculty
  • Department of Bioengineering
  • Institute for Quantitative and Computational Biosciences
  • Jonsson Comprehensive Cancer Center
Director
  • MII Research in Informatics Summer Experience

Office: 924 Westwood Blvd, Suite 420, Room

Phone: (310) 794-3536

E-Mail: whsu@mednet.ucla.edu

http://willhsu.discoveryinformatics.org/

Biography

I am Associate Professor in Residence in the Department of Radiological Sciences and part of the Medical Imaging & Informatics group. I am also a faculty affiliate of the Department of Bioengineering and the Institute of Quantitative and Computational Biosciences (QCB). I actively collaborate with faculty members in the Center for Domain-Specific Computing, Clinical & Translational Science Institute, and UCLA-PKU Joint Research Institute. I currently serve as Chair-Elect of the AMIA Biomedical Imaging Informatics Working Group. I am a Principal Investigator of a four-year, National Science Foundation-funded Smart & Connected Health award applying reinforcement learning approaches to discover optimal care pathways to improve diagnostic accuracy and reduce unnecessary tests.

Reseach Interests

  • Develop machine learning approaches for discovering optimal care pathways for individuals
  • Build software tools and algorithms to enable integrated diagnostics research
  • Use deep neural networks to integrate multimodal data for integrated diagnostics
  • Improve methods for evaluating and adopting prediction models
  • Formalize the process of using published literature for treatment selection and experiment planning

Current Funded Projects

  • Co-Principal Investigator, SCH: INT: Personalized Real-time Learning of Optimal Diagnostic Tests using Multi-modal Clinical Data (NSF 1722516)
  • Investigator, Computer Vision for Detection of Tobacco-Related Diseases on Screening CT (University of California)
  • Investigator, Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary Nodules (NIH/NCI R01 CA210360)
  • Investigator, Accelerator-Rich Architectures with Applications to Healthcare (NSF 1436827)

Publications

2018
  1. Smedley NF, Hsu W. Using deep neural networks for radiogenomic analysis. Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI). Washington, D.C.; 2018.
  2. Shiwen S, Smedley NF, Piedra EAR, Hsu W. Hybrid Hierarchical Model for Lung Cancer Prediction. International Symposium on Biomedical Imaging (ISBI). 2018.
  3. Matiasz NJ, Wood J, Doshi P, Speier W, Beckemeyer B, Wang W, Hsu W, Silva AJ. ResearchMaps.org for integrating and planning research. PLOS One. 2018;13(5):e0195271. DOI: 10.1371/journal.pone.0195271. PDF
2017
  1. Matiasz NJ, Wood J, Wang W, Hsu W, Silva AJ. Translating literature into causal graphs: Toward automated experiment selection. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM). Kansas City, MO; 2017. DOI: 10.1109/BIBM.2017.8217713.
  2. Shen S, Bui AAT, Hsu W. Robust lung nodule classification using 2.5D convolutional neural network. Proc AMIA Fall Symp 2017. Washington, D.C.; 2017.
  3. AR E, Cloughesy T, Ellingson B, El-Saden S, Bui AAT, Hsu W. Evaluating the applicability of tumor probability maps as a resource for improved brain tumor segmentation. Proc Ann Society Neuro-Oncology Scientific Meeting, 2017. San Francisco,California, USA; 2017.
  4. Hsu W, Petousis P, Yu W, Meng F, Bui AAT. A web-based platform for evaluating and disseminating predictive models. 2017 AMIA Joint Summits on Translational Science. San Francisco,California, USA; 2017.
  5. Matiasz NJ, Wood J, Wang W, Silva AJ, Hsu W. Computer-aided experiment planning toward causal discovery in neuroscience. Front Neuroinform. 2017 Feb;11(12). DOI: 10.3389/fninf.2017.00012. PDF
  6. Shen S, Han SX, Petousis P, Weiss RE, Meng F, Bui AAT, Hsu W. A Bayesian model for estimating multi-state disease progression. Comput Biol Med. 2017;81:1111–120. DOI: 10.1016/j.compbiomed.2016.12.011. PDF
  7. Piedra EAR, Ellingson B, Cloughesy T, Taira RK, El-Saden S, Bui AAT, Hsu W. Hybrid Hierarchical Model for Lung Cancer Prediction. International Symposium on Biomedical Imaging (ISBI). 2017.
  8. Piedra EAR, Orosz I, Zide M, El-Saden S, Taira RK, Bui AAT, Hsu W. A Usability Study to Evaluate the Impact of a Novel Automated Brain Tumor Assessment Application. Poster presented at American Medical Informatics Association. 2017.
  9. Piedra EAR, Ellingson B, El-Saden S, Taira RK, Bui AAT, Hsu W. Measuring Tumor Boundary Variability to Improve Automated Segmentation of Brain Tumors Using Multimodal MRI. Poster presented at International Society for Magnetic Resonance in Medicine (ISMRM). 2017.
  10. Piedra EAR, Ellingson B, El-Saden S, Taira RK, Bui AAT, Hsu W. Brain Tumor Segmentation by Variability Characterization of Tumor Boundaries. International Workshop on Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. 2017;:206–216.
2016
  1. Matiasz NJ, Chen W-T, Silva AJ, Hsu W. MedicineMaps: A tool for mapping and linking evidence from experimental and clinical trial literature. AMIA Annu Symp Proc. Chicago, IL; 2016. PDF
  2. Hsu W, Maehara CK, Andrada LP, Beckett KR, McWilliams JP, Moriarty JM, Enzmann DR. Using Time-Driven Activity Based Costing (TDABC) to characterize cost variability in interventional radiology procedures. 2016 Annual Meeting of the Radiological Society of North America. Chicago, IL; 2016.
  3. Piedra EAR, Taira RK, El-Saden S, Ellingson BM, Bui AAT, Hsu W. GlioView: An application that visualizes variability in brain tumor segmentation to inform the clinical assessment of change. 2016 Annual Meeting of the Radiological Society of North America. Chicago, IL; 2016.
  4. Young S, Lo P, Hoffman J, Kim H, Hsu W, Flores C, Lee G, Brown M, McNitt-Gray M. CAD performance on a large cohort of National Lung Screening Trial patients at screening and sub-screening doses. 2016 Annual Meeting of the Radiological Society of North America. Chicago, IL; 2016.
  5. Tong M, Hsu W, Taira RK. A visualization for clinical trial reports: A usability study. AMIA Annu Symp Proc. Chicago, IL; 2016.
  6. Matiasz NJ, Wood J, Hsu W, Silva AJ. ResearchMaps.org: A free web app for integrating and planning experiments. Proceedings of the 15th Annual Molecular and Cellular Cognition Society (MCCS) Symposium. San Diego; 2016. PDF
  7. Shen S, Zhong X, Hsu W, Bui AAT, Wu H, Kuo M, Raman S, Margolis DJA, Sung KH. Quantitative MRI-Driven Deep Learning for Detection of Clinical Significant Prostate Cancer. 24th Intl Soc Magnetic Resonance in Medicine (ISMRM) Annual Meeting. Singapore; 2016.
  8. Wibulpolprasert P, Raman SS, Khoshnoodi P, Yu W, Hsu W, Tan N, Huang J, Lu D, Margolis DJ, Reiter R. MP53-05 Performance of 3T multiparameteric MRI in diagnosis of prostate cancer in comparison with whole mount histopathology: A 5 year experience. Urology [Internet]. 2016;195(4):e698. Retrieved from: http://www.jurology.com/article/S0022-5347(16)00790-4/abstract DOI: http://dx.doi.org/10.1016/j.juro.2016.02.502.
  9. Hsu W, El-Saden S, Taira RK. Medical Imaging Informatics. In: Shen B, Tang H, Jiang X, editors. Translational Biomedical Informatics: A Precision Medicine Perspective. Singapore: Springer; 2016.
  10. Piedra EAR, 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. Biomedical and Health Informatics (BHI), 2016 IEEE-EMBS. Chicago, IL; 2016. DOI: http://dx.doi.org/10.1109/BHI.2016.7455914.
  11. Zaghi S, Alonso J, Orestes M, Kadin N, Hsu W, Berke G. Idiopathic subglottic stenosis: A comparison of tracheal size. Ann Otol Rhinol Laryngol [Internet]. 2016;125(8):622–6. Retrieved from: http://www.jurology.com/article/S0022-5347(16)00790-4/abstract DOI: http://dx.doi.org/10.1016/j.juro.2016.02.502.
  12. Alaa A, Moon K, Hsu W, Schaar M van der. ConfidentCare: A clinical decision support system for personalized breast cancer screening. IEEE Transactions on Multimedia [Internet]. 2016;18(10):1942–55. Retrieved from: http://www.jurology.com/article/S0022-5347(16)00790-4/abstract DOI: http://dx.doi.org/10.1016/j.juro.2016.02.502.
  13. Piedra EAR, Taira RK, El-Saden S, Ellingson B, Bui AAT, Hsu W. GlioView: An Application to Visualize Variability in Brain Tumor Segmentation to Inform the Clinical Assessment of Change. Applied science presentation at Radiological Society of North America (RSNA). 2016.
  14. Piedra EAR, Ho KC, Taira RK, El-Saden S, Ellingson B, Bui AAT, Hsu W. Glioblastoma Multiforme Segmentation by Variability Characterization of Tumor Boundaries. Medical Image Computing and Computer Assisted Intervention Society (MICCAI), MICCAI-BRATS Conference Workshop. 2016.
  15. Piedra EAR, Taira RK, El-Saden S, Ellingson B, Bui AAT, Hsu W. Assessing Variability in Brain Tumor Segmentation to Improve Volumetric Accuracy and Characterization of Change. 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE-EMBS). 2016. p. 380–383.
2015
  1. Matiasz NJ, Silva AJ, Hsu W. Synthesizing clinical trials for evidence-based medicine: A representation of empirical and hypothetical causal relations. Proceedings of the 6th Annual Joint Summits on Translational Science: AMIA Summit on Clinical Research Informatics. San Francisco; 2015. PDF
  2. Nikkola E, Laiwalla A, Ko A, Alvarez M, Connolly M, Ooi YC, Hsu W, Bui AAT, Pajukanta P, Gonzalez NR. Remote ischemic conditioning alters methylation and expression of cell cycle genes in aneurysmal subarachnoid hemorrhage. Stroke. 2015;46:2445–51. DOI: 10.1161/STROKEAHA.115.009618. PDF
  3. Hsu W, Gonzalez NR, Chien A, Villablanca PJ, Pajukanta P, Vinuela F, Bui AAT. An integrated, ontology-driven approach to constructing observational databases for research. J Biomed Inform. 2015;55:132–42. DOI: 10.1016/j.jbi.2015.03.008. PDF
  4. Shen S, Bui AAT, Cong J, Hsu W. An automated lung segmentation approach using bidirectional chain codes to improve nodule detection accuracy. Comput Biol Med. 2015;57:139–49. DOI: 10.1016/j.compbiomed.2014.12.008. PDF
  5. Duggan N, Bae E, Shen S, Hsu W, Bui AAT, Jones E, Glavin M, Vese L. A technique for lung nodule candidate detection in CT using global minimization methods. Energy Minimization Methods in Computer Vision and Pattern Recognition. Springer International Publishing; 2015. PDF
  6. Laviana AA, Ilg AM, Veruttipong D, Tan H-J, Burke MA, Niedzwiecki DR, Kupelian PA, King CR, Steinberg ML, Kundavaram CR, Kamrava M, Kaplan AL, Moriarity AK, Hsu W, Margolis DJA, Hu JC, Saigal CS. Utilizing time-driven activity-based costing to understand the short- and long-term costs of treating localized, low-risk prostate cancer. Cancer. 2015;In press. DOI: 10.1002/cncr.29743. PDF
  7. Abtin F, Suh RD, Nasehi L, Han SX, Hsu W, Quirk M, Genshaft SJ, Gutierrez AJ, Cameron RB. Percutaneous cryoablation for the treatment of recurrent thymoma: Preliminary safety and efficacy. J Vasc Interv Radiol. 2015;26:709–14. DOI: 10.1016/j.jvir.2014.12.024. PDF
  8. Song L, Hsu W, Xu J, Schaar M van der. Using contextual learning to improve diagnostic accuracy: Application in breast cancer screening. IEEE J Biomed Health Inform. 2015; DOI: 10.1109/JBHI.2015.2414934. PDF
  9. Smedley NF, Chau N, Petruse A, Bui AAT, Naeim A, Hsu W. A platform for generating and validating breast risk models from clinical data: Towards patient-centered risk stratified screening. AMIA Annu Symp Proc. San Francisco, CA, USA; 2015.
  10. Shen S, Han SX, Petousis P, Meng F, Bui AAT, Hsu W. Continuous Markov Model Approach Using Individual Patient Data to Estimate Mean Sojourn Time of Lung Cancer. AMIA Annu Symp Proc. San Francisco, CA, USA; 2015.
  11. Hsu W, Han SX, Arnold CW, Bui AAT, Enzmann DR. A data-driven approach for quality assessment of radiologic interpretations. J Am Med Inform Assoc. 2015; DOI: 10.1093/jamia/ocv161.
2014
  1. Matiasz NJ, Hsu W, Silva AJ. ResearchMaps.org, a free web application to track causal information in biology. Proceedings of the 13th Annual Molecular and Cellular Cognition Society (MCCS) Symposium. Washington, D.C.; 2014. PDF
  2. Singleton KW, Bui AAT, Hsu W. Transfer and transport: Incorporating causal methods for improving predictive models. J Am Med Inform Assoc. 2014;21:e374–5. DOI: 10.1136/amiajnl-2014-002968. PDF
  3. Singleton KW, Speier W, Bui AAT, Hsu W. Motivating the additional use of external validity: Examining transportability in a model of glioblastoma multiforme. AMIA Annu Symp Proc. 2014. p. 1930–9. PDF
  4. Garcia-Gathright JI, Meng F, Hsu W. UCLA at TREC 2014 clinical decision support track: Exploring language models, query expansion, and boosting. The Twenty-Third Text REtrieval Conference (TREC 2014). 2014. PDF
  5. Haas BE, Gonzalez NR, Nikkola E, Connolly M, Hsu W, Bui AAT, Vinuela F, Pajukanta P. Feasibility and preliminary results of whole blood RNA-sequencing analysis in patients with intracranial aneurysms. Stroke. 2014;45.
  6. Han SX, Hsu W, Arnold CW, Margolis DJA, Bui AAT, Enzmann DR. RadQA: Automated quality control of radiological interpretations in prostate cancer. RSNA Annual Meeting. Chicago, IL; 2014.
2013
  1. Hsu W, Bui AAT. Leveraging domain knowledge to facilitate visual exploration of large population datasets. AMIA Annu Symp Proc. 2013. p. 615–23. PDF
  2. Bui AAT, Hsu W, Arnold CW, El-Saden S, Aberle DR, Taira RK. Imaging-based observational databases for clinical problem solving: The role of informatics. J Am Med Inform Assoc. 2013;20:1053–8. DOI: 10.1136/amiajnl-2012-001340. PDF
  3. Hsu W, Markey MK, Wang MD. Biomedical imaging informatics in the era of precision medicine: Progress, challenges, and opportunities. J Am Med Inform Assoc. 2013;20:1010–3. DOI: 10.1136/amiajnl-2013-002315. PDF
  4. Tong M, Hsu W, Taira RK. A formal representation for numerical data presented in published clinical trial reports. Stud Health Technol Inform. 2013;192:856–60. DOI: 10.3233/978-1-61499-289-9-856. PDF
  5. Abtin F, Sandberg JK, Suh RD, Hsu W, Sayre JW, Cameron RB. Percutaneous cryoablation in management of recurrent mesothelioma after surgical pleurectomy and decortication: Efficacy and predictors of local recurrence. RSNA Annual Meeting. 2013.
  6. Hsu W, Tong M, Taira RK, Bui AAT. Visualizing evidence in biomedical literature: Integration and application of clinical, imaging, and genomic findings reported in research studies. RSNA Annual Meeting. 2013.
  7. Han SX, Nasehi L, Abtin F, Hsu W. An observational database on thymoma patients for studying cryoablation outcomes. 4th International Thymic Malignancy Interest Group Annual Meeting. 2013.
2012
  1. Hsu W, Speier W, Taira RK. Automated extraction of reported statistical analyses: towards a logical representation of clinical trial literature. AMIA Annu Symp Proc. 2012. p. 350–9. PDF
  2. Singleton KW, Hsu W, Bui AAT. Comparing predictive models of glioblastoma multiforme built using multi-institutional and local data sources. AMIA Annu Symp Proc. 2012. p. 1385–92. PDF
  3. Hsu W, Taira RK, El-Saden S, Kangarloo H, Bui AAT. Context-based electronic health record: toward patient specific healthcare. Information Technology in Biomedicine, IEEE Transactions on. 2012;16:228\textendash234. DOI: 10.1109/TITB.2012.2186149. PDF
  4. Wu JA, Hsu W, Bui AAT. An approach for incorporating context in building probabilistic predictive models. Healthcare Informatics, Imaging and Systems Biology (HISB) 2012 IEEE Second International Conference. San Diego, CA: IEEE; 2012. DOI: 10.1109/HISB.2012.30. PDF
  5. Wu JA, Hsu W, Bui AAT. Extracting relevant information from clinical records: Towards modeling the evolution of intracranial aneurysms. AMIA Annu Symp Proc. 2012. PDF
  6. Tong M, Hsu W, Taira RK. A representation for standardizing numerical data from clinical trial reports. RSNA Annual Meeting. Chicago, IL; 2012.
  7. Wu JA, Hsu W, Taira RK, Bui AAT. A population-based temporal visualization for predicting survival for non-small cell lung cancer. RSNA Annual Meeting. Chicago, IL; 2012.
2011
  1. Hsu W, Taira RK, Vinuela F, Bui AAT. A case-based retrieval system using natural language processing and population-based visualization. Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE International Conference. San Jose, CA; 2011. DOI: 10.1109/HISB.2011.3. PDF
  2. Speier W, Arnold CW, Hsu W, Bui AAT. Content-based image retrieval using feature density estimates. AMIA Annu Symp Proc. Washington DC; 2011. PDF
  3. Hsu W, Sayre JW, Bui AAT, Taira RK. Modeling medical imaging and molecular biology correlates from literature. AMIA Annu Symp Proc. Washington DC; 2011. PDF
  4. Yan M, Zou Y, Hsu W, Chien A, Vese L, Aberle DR, Bui AAT, Cong J. Accelerating medical image reconstruction and analysis using domain specific computing. RSNA Annual Meeting. Chicago, IL; 2011.
2010
  1. Hsu W, Taira RK. Tools for improving the characterization and visualization of changes in neuro-oncology patients. AMIA Annu Symp Proc. 2010;2010:316–20.
  2. Hsu W, Arnold CW, Taira RK. A Neuro-oncology Workstation for Structuring, Modeling, and Visualizing Patient Records. Proceedings of the 1st ACM International Health Informatics Symposium. New York, NY, USA: ACM; 2010. DOI: 10.1145/1882992.1883120.
  3. Hsu W, Bui AAT. Disease Models, Part II: Querying & Applications. Medical Imaging Informatics. Springer; 2010. p. 371\textendash401. DOI: 10.1007/978-1-4419-0385-3_9.
  4. Bui AAT, Hsu W. Chapter 4: Medical Data Visualization: Toward Integrated Clinical Workstations. Medical Imaging Informatics. 2010;:171\textendash240. DOI: 10.1007/978-1-4419-0385-3_4. PDF
  5. Tong M, Wu JA, Chae S, Chern A, Speier W, Hsu W, Taira RK. Computer-assisted systematic review and interactive visualization of published literature. RSNA Annual Meeting. 2010.
2009
  1. Bashyam V, Hsu W, Watt E, Bui AAT, Kangarloo H, Taira RK. Problem-centric organization and visualization of patient imaging and clinical data. Radiographics. 2009;29:331–43. DOI: 10.1148/rg.292085098.
  2. Hsu W, Antani S, Long RL, Neve L, Thoma GR. SPIRS: A Web-based image retrieval system for large biomedical databases. Int J Med Inform. 2009;78 Suppl 1:S13–24. DOI: 10.1016/j.ijmedinf.2008.09.006.
  3. Hsu W, Bui AAT, Taira RK, Kangarloo H. Integrating imaging and clinical data for decision support. Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications. 2009. p. 18\textendash33. DOI: 10.4018/978-1-60566-314-2.ch002.
  4. Watt E, Hsu W, Bui AAT. Visualizing the evolution of clinical features in cancer: Mapping trends to disease outcome for prediction. Radiological Sciences of North America (RSNA). 2009;
2008
  1. Taira RK, Bui AAT, Hsu W, Bashyam V, Dube S, Watt E, Andrada LP, El-Saden S, Cloughesy TF, Kangarloo H. A tool for improving the longitudinal imaging characterization for neuro-oncology cases. AMIA Annu Symp Proc. 2008. p. 712–6.
2007
  1. Hsu W, Aberle DR, El-Saden S, Kangarloo H, Bui AAT. A visual query application for interacting with a probabilistic model of tumor image features. RSNA. Chicago, IL, 2007.
Older
  1. Hsu W, Bui AAT. A framework for visually querying a probabilistic model of tumor image features. AMIA Annu Symp Proc. 2006;2006:354–8.
  2. Hsu W, Dordoni A, El-Saden S, Bui AAT. A visual query interface for assisting in decision support of tumors using image findings structured by Bayesian networks. Proc ARRS. Vancouver, Canada; 2006. p. A31.
  3. Chu W, Hsu C-C, Cardenas AF, Taira RK. Knowledge-based image retrieval with spatial and temporal constructs. Knowledge and Data Engineering, IEEE Transactions on. 1998;10:872\textendash888. DOI: 10.1109/69.738355.