William Hsu

Professor-in-Residence, Radiological Sciences, University of California Los Angeles

William Hsu is Professor of Radiological Sciences and Bioengineering at the University of California, Los Angeles, affiliated with the Medical & Imaging Informatics group. He is a biomedical informatician focused on maximizing the utility of multimodal data to detect and treat cancers earlier. His lab harnesses artificial intelligence/machine learning techniques to integrate and transform multimodal data into actionable knowledge. He serves as principal investigator on grants from the National Institutes of Health (National Cancer Institute, National Institute for Biomedical Imaging and Bioengineering), National Science Foundation, Agency for Healthcare Research and Quality, and the V Foundation. He is a deputy editor of Radiology: Artificial Intelligence and associate editor for the Journal of the American Medical Informatics Association.

Interests

biomedical informatics, imaging informatics, machine learning, lung cancer screening, multimodal data integration

Education and Training

University of California, Los AngelesPhD06/2009Biomedical Engineering, Medical Imaging Informatics
Johns Hopkins UniversityBS06/2004Biomedical Engineering

Awards and Honors

  • Senior Member, IEEE, 2020.
  • Basic Science Teaching Award, Radiological Sciences, UCLA, 2019.

Publications

  1. Inoue K, Hsu W. Transportability Analysis-A Tool for Extending Trial Results to a Representative Target Population.. JAMA network open, 2024.
  2. Rahrooh A, Garlid AO, Bartlett K, Coons W, Petousis P, Hsu W, Bui AAT. Towards a framework for interoperability and reproducibility of predictive models.. Journal of biomedical informatics, 2023.
  3. Prosper AE, Kammer MN, Maldonado F, Aberle DR, Hsu W. Expanding Role of Advanced Image Analysis in CT-detected Indeterminate Pulmonary Nodules and Early Lung Cancer Characterization.. Radiology, 2023.
  4. Ding R, Yadav A, Rodriguez E, Araujo Lemos da Silva AC, Hsu W. Tailoring pretext tasks to improve self-supervised learning in histopathologic subtype classification of lung adenocarcinomas.. Computers in biology and medicine, 2023.
  5. Li S, Zeng W, Ni X, Liu Q, Li W, Stackpole ML, Zhou Y, Gower A, Krysan K, Ahuja P, Lu DS, Raman SS, Hsu W, Aberle DR, Magyar CE, French SW, Han SB, Garon EB, Agopian VG, Wong WH, Dubinett SM, Zhou XJ. Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.. Proceedings of the National Academy of Sciences of the United States of America, 2023.
  6. Lin Y, Liang LJ, Ding R, Prosper AE, Aberle DR, Hsu W. Factors Associated With Nonadherence to Lung Cancer Screening Across Multiple Screening Time Points.. JAMA network open, 2023.
  7. Lin Y, Ding R, Prosper AE, Aberle DR, Bui AAT, Hsu W. Capturing Demographic, Health-Related, and Psychosocial Variables in a Standardized Manner: Towards Improving Cancer Screening Adherence.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2023.
  8. Marasinou C, Li B, Paige J, Omigbodun A, Nakhaei N, Hoyt A, Hsu W. Improving the Quantitative Analysis of Breast Microcalcifications: A Multiscale Approach.. Journal of digital imaging, 2023.
  9. Zabihollahy F, Miao Q, Sonni I, Vangala S, Kim H, Hsu W, Sisk A, Reiter R, Raman S, Sung K. Racial Disparities in Quantitative MRI for African American and White Men with Prostate Cancer.. Research square, 2023.
  10. Paige JS, Lee CI, Wang PC, Hsu W, Brentnall AR, Hoyt AC, Naeim A, Elmore JG. Variability Among Breast Cancer Risk Classification Models When Applied at the Level of the Individual Woman.. Journal of general internal medicine, 2023.
  11. Konz N, Buda M, Gu H, Saha A, Yang J, Chledowski J, Park J, Witowski J, Geras KJ, Shoshan Y, Gilboa-Solomon F, Khapun D, Ratner V, Barkan E, Ozery-Flato M, Martí R, Omigbodun A, Marasinou C, Nakhaei N, Hsu W, Sahu P, Hossain MB, Lee J, Santos C, Przelaskowski A, Kalpathy-Cramer J, Bearce B, Cha K, Farahani K, Petrick N, Hadjiiski L, Drukker K, Armato SG, Mazurowski MA. A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis.. JAMA network open, 2023.
  12. Chen IE, Tsui B, Zhang H, Qiao JX, Hsu W, Nour M, Salamon N, Ledbetter L, Polson J, Arnold C, BahrHossieni M, Jahan R, Duckwiler G, Saver J, Liebeskind D, Nael K. Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.. Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences, 2022.
  13. Hsu W, Hippe DS, Nakhaei N, Wang PC, Zhu B, Siu N, Ahsen ME, Lotter W, Sorensen AG, Naeim A, Buist DSM, Schaffter T, Guinney J, Elmore JG, Lee CI. External Validation of an Ensemble Model for Automated Mammography Interpretation by Artificial Intelligence.. JAMA network open, 2022.
  14. Hendrix N, Lowry KP, Elmore JG, Lotter W, Sorensen G, Hsu W, Liao GJ, Parsian S, Kolb S, Naeim A, Lee CI. Radiologist Preferences for Artificial Intelligence-Based Decision Support During Screening Mammography Interpretation.. Journal of the American College of Radiology : JACR, 2022.
  15. Marathe K, Marasinou C, Li B, Nakhaei N, Li B, Elmore JG, Shapiro L, Hsu W. Automated quantitative assessment of amorphous calcifications: Towards improved malignancy risk stratification.. Computers in biology and medicine, 2022.
  16. Inoue K, Watson KE, Kondo N, Horwich T, Hsu W, Bui AAT, Duru OK. Association of Intensive Blood Pressure Control and Living Arrangement on Cardiovascular Outcomes by Race: Post Hoc Analysis of SPRINT Randomized Clinical Trial.. JAMA network open, 2022.
  17. Dumont RA, Palma Diaz MF, Hsu W, Sepahdari AR. Olfactory Neuroblastoma: Re-Evaluating the Paradigm of Intracranial Extension and Cyst Formation.. Diagnostics (Basel, Switzerland), 2022.
  18. Lin Y, Fu M, Inoue K, Jeon CY, Hsu W. Response to Letter to the Editor.. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2022.
  19. Hsu W, Sohn JH. Using Radiomics for Risk Stratification: Where We Need to Go.. Radiology, 2021.
  20. Lin Y, Fu M, Ding R, Inoue K, Jeon CY, Hsu W, Aberle DR, Prosper AE. Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis.. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2021.
  21. Inoue K, Hsu W, Arah OA, Prosper AE, Aberle DR, Bui AAT. Generalizability and Transportability of the National Lung Screening Trial Data: Extending Trial Results to Different Populations.. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2021.
  22. Hsu W, Baumgartner C, Deserno TM, Section Editors of the IMIA Yearbook Section on Sensors, Signals, and Imaging Informatics. Notable Papers and New Directions in Sensors, Signals, and Imaging Informatics.. Yearbook of medical informatics, 2021.
  23. Prosper AE, Inoue K, Brown K, Bui AAT, Aberle D, Hsu W. Association of Inclusion of More Black Individuals in Lung Cancer Screening With Reduced Mortality.. JAMA network open, 2021.
  24. Matiasz NJ, Wood J, Wang W, Silva AJ, Hsu W. Experiment Selection in Meta-Analytic Piecemeal Causal Discovery.. IEEE access : practical innovations, open solutions, 2021.
  25. Peterson E, May FP, Kachikian O, Soroudi C, Naini B, Kang Y, Myint A, Guyant G, Elmore J, Bastani R, Maehara C, Hsu W. Automated identification and assignment of colonoscopy surveillance recommendations for individuals with colorectal polyps.. Gastrointestinal endoscopy, 2021.
  26. Smedley NF, Aberle DR, Hsu W. Using deep neural networks and interpretability methods to identify gene expression patterns that predict radiomic features and histology in non-small cell lung cancer.. Journal of medical imaging (Bellingham, Wash.), 2021.
  27. Myint A, Corona E, Yang L, Nguyen BS, Lin C, Huang MZ, Shao P, Mwengela D, Didero M, Asokan I, Bui AAT, Hsu W, Maehara C, Naini BV, Kang Y, Bastani R, May FP. Gastroenterology visitation and reminders predict surveillance uptake for patients with adenomas with high-risk features.. Scientific reports, 2021.
  28. Emaminejad N, Wahi-Anwar MW, Kim GHJ, Hsu W, Brown M, McNitt-Gray M. Reproducibility of lung nodule radiomic features: Multivariable and univariable investigations that account for interactions between CT acquisition and reconstruction parameters.. Medical physics, 2021.
  29. Gao Y, Kalbasi A, Hsu W, Ruan D, Fu J, Shao J, Cao M, Wang C, Eilber FC, Bernthal N, Bukata S, Dry SM, Nelson SD, Kamrava M, Lewis J, Low DA, Steinberg M, Hu P, Yang Y. Treatment effect prediction for sarcoma patients treated with preoperative radiotherapy using radiomics features from longitudinal diffusion-weighted MRIs.. Physics in medicine and biology, 2020.
  30. Hsu W, Baumgartner C, Deserno TM, Section Editors for the IMIA Yearbook Section on Sensors, Signals, and Imaging Informatics. Notable Papers and Trends from 2019 in Sensors, Signals, and Imaging Informatics.. Yearbook of medical informatics, 2020.
  31. Ho DR, Luery SE, Ghosh RM, Maehara CK, Silvestro E, Whitehead KK, Sze RW, Hsu W, Nguyen KL. Cardiovascular 3-D Printing: Value-Added Assessment Using Time-Driven Activity-Based Costing.. Journal of the American College of Radiology : JACR, 2020.
  32. Smedley NF, El-Saden S, Hsu W. Discovering and interpreting transcriptomic drivers of imaging traits using neural networks.. Bioinformatics (Oxford, England), 2020.
  33. Lin Y, Wei L, Han SX, Aberle DR, Hsu W. EDICNet: An end-to-end detection and interpretable malignancy classification network for pulmonary nodules in computed tomography.. Proceedings of SPIE--the International Society for Optical Engineering, 2020.
  34. Wibulpolprasert P, Raman SS, Hsu W, Margolis DJA, Asvadi NH, Khoshnoodi P, Moshksar A, Tan N, Ahuja P, Maehara CK, Sisk A, Sayre J, Lu DSK, Reiter RE. Influence of the Location and Zone of Tumor in Prostate Cancer Detection and Localization on 3-T Multiparametric MRI Based on PI-RADS Version 2.. AJR. American journal of roentgenology, 2020.
  35. Li M, Hsu W, Xie X, Cong J, Gao W. SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network.. IEEE transactions on medical imaging, 2020.
  36. Hsu W, Elmore JG. Shining Light Into the Black Box of Machine Learning.. Journal of the National Cancer Institute, 2019.
  37. Omigbodun AO, Noo F, McNitt-Gray M, Hsu W, Hsieh SS. The effects of physics-based data augmentation on the generalizability of deep neural networks: Demonstration on nodule false-positive reduction.. Medical physics, 2019.
  38. Hsu W, Baumgartner C, Deserno T, Section Editors for the IMIA Yearbook Section on Sensors, Signals, and Imaging Informatics. Advancing Artificial Intelligence in Sensors, Signals, and Imaging Informatics.. Yearbook of medical informatics, 2019.
  39. Petousis P, Winter A, Speier W, Aberle DR, Hsu W, Bui AAT. Using Sequential Decision Making to Improve Lung Cancer Screening Performance.. IEEE access : practical innovations, open solutions, 2019.
  40. Hsu W, Hoyt AC. Using Time as a Measure of Impact for AI Systems: Implications in Breast Screening.. Radiology. Artificial intelligence, 2019.
  41. Wibulpolprasert P, Raman SS, Hsu W, Margolis DJA, Asvadi NH, Khoshnoodi P, Moshksar A, Tan N, Ahuja P, Maehara CK, Huang J, Sayre J, Lu DSK, Reiter RE. Detection and Localization of Prostate Cancer at 3-T Multiparametric MRI Using PI-RADS Segmentation.. AJR. American journal of roentgenology, 2019.
  42. Winter A, Aberle DR, Hsu W. External validation and recalibration of the Brock model to predict probability of cancer in pulmonary nodules using NLST data.. Thorax, 2019.
  43. Petousis P, Han SX, Hsu W, Bui AAT. Generating Reward Functions Using IRL Towards Individualized Cancer Screening.. Artificial intelligence in health : first International Workshop, AIH 2018, Stockholm, Sweden, July 13-14, 2018, Revised selected papers. AIH (Workshop) (1st : 2018 : Stockholm, Sweden), 2019.
  44. Shen S, Han SX, Aberle DR, Bui AA, Hsu W. An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification.. Expert systems with applications, 2019.
  45. Faiena I, Salmasi A, Mendhiratta N, Markovic D, Ahuja P, Hsu W, Elashoff DA, Raman SS, Reiter RE. PI-RADS Version 2 Category on 3 Tesla Multiparametric Prostate Magnetic Resonance Imaging Predicts Oncologic Outcomes in Gleason 3 + 4 Prostate Cancer on Biopsy.. The Journal of urology, 2019.
  46. Faiena I, Salmasi A, Mendhiratta N, Markovic D, Ahuja P, Hsu W, Elashoff DA, Raman SS, Reiter RE. PI-RADS Version 2 Category on 3 Tesla Multiparametric Prostate Magnetic Resonance Imaging Predicts Oncologic Outcomes in Gleason 3 + 4 Prostate Cancer on Biopsy.. The Journal of urology, 2019.
  47. Petousis P, Naeim A, Mosleh A, Hsu W. Evaluating the Impact of Uncertainty on Risk Prediction: Towards More Robust Prediction Models.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018.
  48. Johnson DC, Raman SS, Mirak SA, Kwan L, Bajgiran AM, Hsu W, Maehara CK, Ahuja P, Faiena I, Pooli A, Salmasi A, Sisk A, Felker ER, Lu DSK, Reiter RE. Detection of Individual Prostate Cancer Foci via Multiparametric Magnetic Resonance Imaging.. European urology, 2018.
  49. Smedley NF, Ellingson BM, Cloughesy TF, Hsu W. Longitudinal Patterns in Clinical and Imaging Measurements Predict Residual Survival in Glioblastoma Patients.. Scientific reports, 2018.
  50. Hsu W, Zhou X, Petruse A, Chau N, Lee-Felker S, Hoyt A, Wenger N, Elashoff D, Naeim A. Role of Clinical and Imaging Risk Factors in Predicting Breast Cancer Diagnosis Among BI-RADS 4 Cases.. Clinical breast cancer, 2018.
  51. Arevian AC, Bell D, Kretzman M, Kasari C, Narayanan S, Kesselman C, Wu S, Di Capua P, Hsu W, Keener M, Pevnick J, Wells KB, Chung B. Participatory methods to support team science development for predictive analytics in health.. Journal of clinical and translational science, 2018.
  52. Hsu W, Deserno TM, Kahn CE, Section Editors for the IMIA Yearbook Section on Sensor, Signal and Imaging Informatics. Sensor, Signal, and Imaging Informatics in 2017.. Yearbook of medical informatics, 2018.
  53. Smedley NF, Hsu W. USING DEEP NEURAL NETWORKS FOR RADIOGENOMIC ANALYSIS.. Proceedings. IEEE International Symposium on Biomedical Imaging, 2018.
  54. 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.
  55. Tan N, Shen L, Khoshnoodi P, Alcalá HE, Yu W, Hsu W, Reiter RE, Lu DY, Raman SS. Pathological and 3 Tesla Volumetric Magnetic Resonance Imaging Predictors of Biochemical Recurrence after Robotic Assisted Radical Prostatectomy: Correlation with Whole Mount Histopathology.. The Journal of urology, 2017.
  56. Hsu W, Park S, Kahn CE. Sensor, Signal, and Imaging Informatics.. Yearbook of medical informatics, 2017.
  57. Young S, Lo P, Kim G, Brown M, Hoffman J, Hsu W, Wahi-Anwar W, Flores C, Lee G, Noo F, Goldin J, McNitt-Gray M. The effect of radiation dose reduction on computer-aided detection (CAD) performance in a low-dose lung cancer screening population.. Medical physics, 2017.
  58. Matiasz NJ, Wood J, Wang W, Silva AJ, Hsu W. Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.. Frontiers in neuroinformatics, 2017.
  59. Tong M, Hsu W, Taira RK. Evaluating a Novel Summary Visualization for Clinical Trial Reports: A Usability Study.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017.
  60. Shen S, Han SX, Petousis P, Weiss RE, Meng F, Bui AA, Hsu W. A Bayesian model for estimating multi-state disease progression.. Computers in biology and medicine, 2016.
  61. Abtin F, Quirk MT, Suh RD, Hsu W, Han SX, Kim GJ, Genshaft S, Sandberg JK, Olevsky O, Cameron RB. Percutaneous Cryoablation for the Treatment of Recurrent Malignant Pleural Mesothelioma: Safety, Early-Term Efficacy, and Predictors of Local Recurrence.. Journal of vascular and interventional radiology : JVIR, 2016.
  62. 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 International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics, 2016.
  63. Zaghi S, Alonso J, Orestes M, Kadin N, Hsu W, Berke G. Idiopathic Subglottic Stenosis: A Comparison of Tracheal Size.. The Annals of otology, rhinology, and laryngology, 2016.
  64. Katrib A, Hsu W, Bui A, Xing Y. "RADIOTRANSCRIPTOMICS": A synergy of imaging and transcriptomics in clinical assessment.. Quantitative biology (Beijing, China), 2016.
  65. Hsu W, El-Saden S, Taira RK. Medical Imaging Informatics.. Advances in experimental medicine and biology, 2016.
  66. Hsu W, Han SX, Arnold CW, Bui AA, Enzmann DR. A data-driven approach for quality assessment of radiologic interpretations.. Journal of the American Medical Informatics Association : JAMIA, 2015.
  67. Laviana AA, Ilg AM, Veruttipong D, Tan HJ, Burke MA, Niedzwiecki DR, Kupelian PA, King CR, Steinberg ML, Kundavaram CR, Kamrava M, Kaplan AL, Moriarity AK, Hsu W, Margolis DJ, 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.
  68. Nikkola E, Laiwalla A, Ko A, Alvarez M, Connolly M, Ooi YC, Hsu W, Bui A, Pajukanta P, Gonzalez NR. Remote Ischemic Conditioning Alters Methylation and Expression of Cell Cycle Genes in Aneurysmal Subarachnoid Hemorrhage.. Stroke, 2015.
  69. Abtin F, Suh RD, Nasehi L, Han SX, Hsu W, Quirk M, Genshaft S, Gutierrez AJ, Cameron RB. Percutaneous cryoablation for the treatment of recurrent thymoma: preliminary safety and efficacy.. Journal of vascular and interventional radiology : JVIR, 2015.
  70. Hsu W, Gonzalez NR, Chien A, Pablo Villablanca J, Pajukanta P, Viñuela F, Bui AA. An integrated, ontology-driven approach to constructing observational databases for research.. Journal of biomedical informatics, 2015.
  71. Song L, Hsu W, Xu J, van der Schaar M. Using Contextual Learning to Improve Diagnostic Accuracy: Application in Breast Cancer Screening.. IEEE journal of biomedical and health informatics, 2015.
  72. Shen S, Bui AA, Cong J, Hsu W. An automated lung segmentation approach using bidirectional chain codes to improve nodule detection accuracy.. Computers in biology and medicine, 2014.
  73. Singleton KW, Speier W, Bui AA, Hsu W. Motivating the additional use of external validity: examining transportability in a model of glioblastoma multiforme.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2014.
  74. Singleton KW, Bui AA, Hsu W. Transfer and transport: incorporating causal methods for improving predictive models.. Journal of the American Medical Informatics Association : JAMIA, 2014.
  75. Genco RJ, Schifferle RE, Dunford RG, Falkner KL, Hsu WC, Balukjian J. Screening for diabetes mellitus in dental practices: a field trial.. Journal of the American Dental Association (1939), 2014.
  76. Hsu W, Bui AA. Leveraging domain knowledge to facilitate visual exploration of large population datasets.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013.
  77. Hsu W, Markey MK, Wang MD. Biomedical imaging informatics in the era of precision medicine: progress, challenges, and opportunities.. Journal of the American Medical Informatics Association : JAMIA, 2013.
  78. Bui AA, Hsu W, Arnold C, El-Saden S, Aberle DR, Taira RK. Imaging-based observational databases for clinical problem solving: the role of informatics.. Journal of the American Medical Informatics Association : JAMIA, 2013.
  79. Tong M, Hsu W, Taira RK. A formal representation for numerical data presented in published clinical trial reports.. Studies in health technology and informatics, 2013.
  80. Wu JA, Hsu W, Bui AA. An Approach for Incorporating Context in Building Probabilistic Predictive Models.. Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, 2012.
  81. Hsu W, Speier W, Taira RK. Automated extraction of reported statistical analyses: towards a logical representation of clinical trial literature.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012.
  82. Singleton KW, Hsu W, Bui AA. Comparing predictive models of glioblastoma multiforme built using multi-institutional and local data sources.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012.
  83. Hsu W, Taira RK, El-Saden S, Kangarloo H, Bui AA. Context-based electronic health record: toward patient specific healthcare.. IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society, 2012.
  84. Hsu W, Taira RK, Viñuela F, Bui AA. A Case-based Retrieval System using Natural Language Processing and Population-based Visualization.. Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, 2011.
  85. Hsu W, Taira RK. Tools for improving the characterization and visualization of changes in neuro-oncology patients.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2010.
  86. Hsu W, Arnold CW, Taira RK. A Neuro-Oncology Workstation for Structuring, Modeling, and Visualizing Patient Records.. IHI ... : proceedings of the ... ACM SIGHIT International Health Informatics Symposium. ACM SIGHIT International Health Informatics Symposium, 2010.
  87. Peterson C, Phillips L, Linden A, Hsu W. Vertebral artery hypoplasia: prevalence and reliability of identifying and grading its severity on magnetic resonance imaging scans.. Journal of manipulative and physiological therapeutics, 2010.
  88. Bashyam V, Hsu W, Watt E, Bui AA, Kangarloo H, Taira RK. Problem-centric organization and visualization of patient imaging and clinical data.. Radiographics : a review publication of the Radiological Society of North America, Inc, 2009.
  89. Hsu W, Antani S, Long LR, Neve L, Thoma GR. SPIRS: a Web-based image retrieval system for large biomedical databases.. International journal of medical informatics, 2008.
  90. Taira RK, Taira R, Bui A, Bui AA, Hsu W, Bashyam V, Dube S, Watt E, Andrada L, El-Saden S, Cloughesy T, Kangarloo H. A tool for improving the longitudinal imaging characterization for neuro-oncology cases.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2008.
  91. Hsu W, Long LR, Antani S. SPIRS: a framework for content-based image retrieval from large biomedical databases.. Studies in health technology and informatics, 2007.
  92. Hsu W, Bui AA. A framework for visually querying a probabilistic model of tumor image features.. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2006.