Profile
Dr. Song’s research interests lie in biomedical informatics, machine learning and statistical learning algorithms, data mining and knowledge discovery. Her long-term research goal is to use novel computational algorithms to discover clinically meaningful knowledge from integrated healthcare databases and apply that knowledge to understand and improve population health. During her postdoctoral training, she developed various machine learning models for predicting chronic kidney disease onset in the diabetic population from electronic medical records (EMRs) and a robust risk factor identification framework based on EMRs and external registries. As a research assistant professor, she leveraged clinical data infrastructure for research as well as providing informatics support for the PCORnet Greater Plains Collaborative (GPC), leading the GPC Reusable Observable Unified Study Environment (GROUSE) project. Dr. Song is involved with multiple projects funded by BioNexus, CTSA, PCORI, NIH, which involve developing algorithms and analytical packages for cohort identification and knowledge discovery for a variety of acute or chronic health conditions including COVID-19. She continues to pursue methodological advancement on mining “big” medical data and developing better predictive and prescriptive analytical models, as well as seek further infrastructural improvement for GROUSE with elastic cloud computing capability.
Academic Information
Office
1 Hospital Dr.
Columbia, MO 65212
United States
Education & Training
Postdoctoral Fellow
2017 – 2019 University of Kansas Medical Center, Medical Informatics
PhD Mathematics
2013 – 2016 University of Missouri-Kansas City
Master of Science, Mathematics and Statistics
2012 – 2013 University of Missouri-Kansas City
Honored Bachelor of Commerce
2007 – 2012 McMaster University
Awards & Honors
- GTA Superior Teaching Award (School of Graduate Studies, UMKC, 2015)
- Certificate of completion with distinction on Principles of Computing
- (Coursera-Rice University, May, 2014)
- On Dean’s honor list (McMaster University, 2010-2012)
Professional Societies and Affiliations
- Member of American Medical Informatics Association
- Member of American Statistical Association
- Member of American Mathematics Society
- Omicron Delta Kappa Honor Society (Invitation)
- The Honor Society of Phi Kappa Phi (Invitation)
Publications
- L.R. Waitman, D.L. Walpitage, D.C. Connolly, L. Patel, M. Liu, X. Song, M.C.Schroeder, J.J. VanWormer, A.S.Mosa, A.M.Davis. Enhancing Data Completeness by Integrating Multi-state Insurance Claims with Electronic Health Records and the Relative Strengths of Administrative and Clinical data to Support Obesity Comparative Effectiveness Research.
In preparation. - R. Wang, Z.Q. Miao, T.M. Liu, M. Liu, K. Grdinovac, X. Song, Y. Liang, D. Delen, and W. Paiva.
Derivation and Validation of Essential Predictors and Risk Index for Early Detection of Diabetic Retinopathy Using Electronic Health Records.
Submitted to J. Clin. Med. In January 2021 - A. Furmanchuk, M. Liu, X. Song, L.R. Waitman, J.R. Meurer, K. Osinski, A. Stoddard, E. Chrischilles, J.C. McClay, L.G. Cowell, U. Tachinardi, P.J. Embi, A.S.M. Mosa, V. Mandhadi, R.C. Shah, D. Garcia, F. Angulo, A. Patino, W.E. Trick, T. Markossian, L.J. Rasmussen-Torvik, A.N. Kho, B.S. Black.
The Effect of the Affordable Care Act on Outpatient Visits by Low-Income established Patients at Major Health Centers.
Submitted to BMJ in November 2020. - A. Furmanchuk, M. Liu, X. Song, L.R. Waitman, J.R. Meurer, K. Osinski, A. Stoddard, E. Chrischilles, J.C. McClay, L.G. Cowell, U. Tachinardi, P.J. Embi, A.S.M. Mosa, V. Mandhadi, R.C. Shah, D. Garcia, F. Angulo, A. Patino, W.E. Trick, T. Markossian, L.J. Rasmussen-Torvik, A.N. Kho, B.S. Black.
The Effect of the Affordable Care Act on Diabetes Care at Major Health Centers: New Patients, Newly Detected Diabetes, and Diabetes Medication Management.
Submitted to BMJ in November 2020. - R. Bisary, X. Song, J. Salle, M. Liu, A. Patel, S.Q. Simpson.
Timing and Progression to Septic Shock Among Emergency Department Patients with Suspected Infection.
Submitted to CHEST in December 2020 - X. Song, M. Liu, L.R. Waitman, A. Patel, S.Q. Simpson
Clinical Features Associated with Rapid Treatment for Sepsis.
Submitted to PLOS One in Jul. 2020 - X. Song, A. S.L. Yu, J.A. Kellum, L.R. Waitman, M.E. Matheny, S.Q. Simpson, Y. Hu, M. Liu.
Transportability of an Explainable Artificial Intelligence Model for Acute Kidney Injury Prediction.
Nat Commun. 2020. 11, 5668 - X. Song, L.R. Waitman, Y. Hu, M. Liu.
The Impact of Medical Big Data Anonymization on Early Acute Kidney Injury Risk Prediction
Accepted by American Medical Informatics Association Informatics Summits 2020. Houston. - X. Song, Lemuel R. Waitman, Alan S.L. Yu, David C. Robbins, Yong Hu, Mei Liu.
Longitudinal risk prediction of chronic kidney disease in diabetic patients using temporal-enhanced gradient boosting machine: retrospective cohort study.
JMIR Medical Informatics. 2020. 8(1):e15510. - X. Song, L.R. Waitman, Y. Hu, ASL. Yu, D. Robbins, M. Liu.
Building predictive models for diabetic kidney disease: an exploration of ontology-based EMR data abstraction.
American Medical Informatics Association Informatics Summits Transl. Sci. Proc. 2019:704-713. - X. Song, L.R. Waitman, Y. Hu, ASL. Yu, D. Robbins, M. Liu.
Robust Clinical Market Identification for Diabetic Kidney Disease with Ensemble Feature Selection.
Journal of the American Medical Informatics Association. 2019. 26(3):242-253.
Abstracts, Presentations and Posters
- X. Song, L. Patel, L.R. Waitman, M. Liu.
Multi-view Gradient Boosting Tree for Acute Kidney Injury Prediction and Modifiable Risk Factor Identification.
AMIA Annual Symposium. Virtual, Nov, 2020 - X. Song, M. Liu, L.R. Waitman, A. Patel, S. Parashar, S.Q. Simpson
Discovery of Clinical Factors Associated with Suspected Infection.
AMIA Annual Symposium. Virtual, Nov, 2020 - W. Dunn, X. Song, M. Lowrance, D. Koestler, A. Komatz, GJ. Chen, E. Al-Hihi, K. Grdinovac, RM. Taylor, MS. Olyaee, SA. Weinman.
Patients with Type 2 Diabetes (T2D) and Elevated Fibrosis-4 Index (FIB-4) under-referred to hepatology and have underrecognized hepatic decompensation complications.
AASLD Conference 2020. Virtual, Nov. 2020. - R. Mousa, A. Dias, X. Song, LA. Clough, F. Merino, W. El Atrouni.
Outcomes of HIV-associated lymphoma treatments: a contemporary single center cohort study.
IDWeek 2020. Virtual, Oct. 2020. - H. Dharia, D. Hayley, C. Burkhardt, X. Song
Do No Harm: Institutional experience of central nervous system (CNS)-active medications (CAMs) prescription per Beers criteria update.
AASLD Conference 2020. KUMC Resident Research Day. Kansas City, KS, Mar. 2020. - X. Song, M. Liu, L.R. Waitman, A. Patel, S. Parashar, S.Q. Simpson
Discovery of Clinical Factors Associated with Suspected Infection.
Critical Care Medicine, Society of Critical Care Medicine. 2020;48(1):784. - S. Parashar, X. Song, M. Liu, & S.Q. Simpson,
Comparison of Severe Sepsis and Sofa for Predicting Outcomes of ED Patients with Suspected Infection.
Critical Care Medicine, Society of Critical Care Medicine, 48(1), 768. - X. Song,
Green HERON in Action.
3rd Frontiers Informatic Meetup. Kansas City, KS. Dec. 2019 - X. Song, L.R. Waitman, M. Liu, L. Walpitage, D. Connolly, L. Patel, M. Schroeder.
GROUSE 2019 Status.
2019 GPC Learning Engagement Conference. Kansas City, MO, Oct. 2019 - X. Song, M. Liu, L.R. Waitman, A. Patel, S.Q. Simpson
Discovering Factors Inducing Rapid Treatment of Sepsis.
American Thoracic Society 2019 International Conference. Dallas, TX, May 2019. - X. Song
A Demonstration on Cohort Discovery of Acute Kidney Injury Patients.
1st Frontiers Informatic Meetup. Kansas City, KS. Mar. 2019 - X. Song, M. Liu, L.R. Waitman, A. Patel, S.Q. Simpson.
Visualization of Clinical Pathways for Severe Sepsis Patients.
American Medical Informatics Association Informatics Summit (AMIA’19). San Francisco CA, March 2019.