Jeffrey A. Thompson, Ph.D.

Professional Background

Dr. Thompson is an Associate Professor of Biostatistics & Data Science and joint Chief Research Informatics Officer for the University of Kansas Medical Center (KUMC) and the University of Kansas Health System. He earned his PhD in Quantitative Biomedical Science from Dartmouth College and is an expert in artificial intelligence and machine learning. Prior to working in academia, Dr. Thompson spent over a decade running a personal health informatics company that provided intuitive data products to people with dietary restrictions (such as Celiac Disease). In 2017, he joined KUMC in the Department of Biostatistics and led the development of the data science curriculum.

After joining the Department, Dr. Thompson co-led the creation of the Curated Cancer Clinical Outcomes Database (C3OD) for KU Cancer Center. C3OD is a tool that allows researchers to easily identify cohorts of patients that might qualify for clinical trials. C3OD is now a required step for cancer clinical trials, leading to more successful accrual.

In 2021, Dr. Thompson became Chief Research Informatics Officer and is working to modernize the digital research infrastructure at KUMC. This includes the creation of a centralized cloud-based research data lakehouse; the provision of Databricks as a HIPAA compliant data analytics platform; and the integration of many research systems in this platform, including electronic data capture systems, biospecimen management, medical records, EKG systems, clinical imaging, and more. This digital research platform helps to position KUMC as a national leader in healthcare research and established a culture of continuous improvement, for example, with the upcoming rollout of an electronic lab notebook.

Dr. Thompson’s data science teaching led to him winning the KU Edwards Campus Faculty Teaching Excellence Award in 2021 and his commitment to continuing education earned him the Department of Urology Teacher Appreciation Award in 2022. He continues to focus on giving staff and faculty chances to upskill, with the creation of an Artificial Intelligence summer workshop that began in 2023.

In addition to this other roles, Dr. Thompson serves as the co-lead for the Informatics Core of the Frontiers Clinical and Translational Science Institute, the Associate Director of the Quantitative Omics Core for the Kansas Institute of Precision Medicine, and the EHR and Clinical Informatics Leader for the All of Us Research Program Heartland Consortium.

• BS, Computer Science, University of Southern Maine, Portland, ME
• PhD, Quantitative Biomedical Science, Dartmouth College, Hanover, NH

• American Statistical Association, Member, 2017 - Present

Research

Overview

Dr. Thompson's research spans AI, machine learning, and informatics. He leverages his expertise in machine learning and AI to develop novel predictive and prognostic models in healthcare settings, with a focus on integrating disparate types of data to enhance prediction or exploiting latent data structure to enhance model performance. Furthermore, he applies machine learning methods to genomic data to identify the possible functional changes that influence disease. In the informatics space, Dr. Thompson works on developing intuitive tools for researchers to use, such as C3OD, improving workflows and providing meaningful data.

• Mudaranthakam, Dinesh., Pal, Thompson, Jeffrey, Hu, Jinxiang, Pei, Dong, Chintala, Shanthan., Reddy, Park, Michele, Fridley, Brooke., L, Gajewski, Byron, Koestler, Devin., C, Mayo, Matthew., S. 2018. A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials. JAMIA Open, 1 (2), 166-171. https://doi.org/10.1093/jamiaopen/ooy023
• Thompson, Jeffrey., A., Koestler, Devin., C.. 2020. Equivalent Change Enrichment Analysis: Assessing Equivalent and Inverse Change in Biological Pathways between Diverse Experiments. BMC Genomics, 21 (1), 180. https://bmcgenomics.biomedcentral.com/track/pdf/10.1186/s12864-020-6589-x
• Thompson, J.., A., Christensen, B.., C., Marsit, C.., J.. 2018. Methylation-to-Expression Feature Models of Breast Cancer Accurately Predict Overall Survival, Distant-Recurrence Free Survival, and Pathologic Complete Response in Multiple Cohorts. Scientific Reports, 8. https://www.nature.com/articles/s41598-018-23494-0
• Thompson, Jeffrey., A., Christensen, Brock., C., Marsit, Carmen., J.. 2018. Pan-Cancer Analysis Reveals Differential Susceptibility of Bidirectional Gene Promoters to DNA Methylation, Somatic Mutations, and Copy Number Alterations. International Journal of Molecular Sciences, 19 (8), 2296. https://doi.org/10.3390/ijms19082296
• Thompson, Jeffrey., A, Hu, Jinxiang, Mudaranthakam, Dinesh., Pal, Streeter, David, Neums, Lisa, Park, Michele, Koestler, Devin., C, Gajewski, Byron, Jensen, Roy, Mayo, Matthew., S. 2019. Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records. Scientific Reports, 9 (1), 9253. https://doi.org/10.1038/s41598-019-45705-y
• Mudaranthakam, Dinesh., Pal, Shergina, Elena, Thompson, Jeffrey, Streeter, David, Hu, Jinxiang, Gajewski, Byron, Koestler, Devin., C., Godwin, Andrew, Jensen, Roy, Mayo, Matthew., S.. 2019. Optimizing Retrieval of Biospecimens Using the Curated Cancer Clinical Outcomes Database (C3OD). Cancer Informatics, 18. https://doi.org/10.1177/1176935119886831
• Mudaranthakam, Dinesh., Pal, Krebill, Ron, Singh, Ravi., D., Price, Cathy, Thompson, Jeffrey, Gajewski, Byron, Koestler, Devin, Mayo, Matthew., S.. 2019. Case Study: Electronic Data Capture System Validation at an Academic Institution. Data Basics, 25 (2)
• Elsarraj, Hanan, Hong, Yan, Limback, Darlene, Zhao, Ruonan, Berger, Jenna, Bishop, Stephanie, Sabbagh, Aria, Oppenheimer, Linzi, Harper, Haleigh., E, Tsimelzon, Anna, Huang, Shixia, Hilsenbeck, Susan, Edwards, Dean, Fontes, Joseph, Fan, Fang, Madan, Rashna, Fangman, Ben, Ellis, Ashley, Tawfik, Ossama, Persons, Diane, Fields, Timothy, Godwin, Andrew, Hagan, Christy, Swenson-Fields, Katherin, Coarfa, Cristian, Thompson, Jeffrey, Behbod, Fariba. 2020. BCL9/STAT3 regulation of transcriptional enhancer networks promote DCIS progression. npj Breast Cancer, 6 (1). https://doi.org/10.1038/s41523-020-0157-z
• Meier, Richard, Thompson, Jeffrey., A., Chung, Mei, Zhao, Naisi, Kelsey, Karl., T., Michaud, Dominique., S., Koestler, Devin., C.. 2019. Bayesian framework for identifying consistent patterns of microbial abundance between body sites. . Statistical Applications in Genetics and Molecular Biology, 18 (6). https://www.degruyter.com/document/doi/10.1515/sagmb-2019-0027/html
• Steigerwalt, Kristy, Fitterling, Lori, Harvey, Mariah, Kartonis, Sarah., McQueeny, DeGeus, Marilyn, Franco, Nora, Thompson, Marie, Sykes-Berry, Sue, Mullaly-Quijas, Peggy, Thompson, Jeffrey., A. 2018. Health Sciences Patron Preference for Library Spaces: A Multi-Site Observational Study. Medical References Services Quarterly. https://www.tandfonline.com/doi/full/10.1080/02763869.2018.1548890?scroll=top&needAccess=true