Jonathan L. Lustgarten, MS, PhD, VMD
I joined DBMI on the urging of one of my advisors as my interests was the combination of data and medicine. This would forever change the course of my career as during my time at DBMI, I learned the tools, techniques, and even more importantly how to employ them for new discovery. I learned how to conduct inter-disciplinary studies combining experts across multiple domains, how to get to the root of a question to begin the approach in solving it, and importantly, how to ask the next question to keep the momentum going. All of this was only made possible because of the people I have been fortunate to work with there. All the experiences, even the courses I took for knowledge increase, has helped me in my career helping integrate biomedical informatics into veterinary medicine.
Student Inspiration Award, University of Pennsylvania School of Veterinary Medicine, 2011
- $100,00 equity free award
Launcelott, ZA, Lustgarten, JL, Sung, J, Samuels, S, Davis, S, Davis, GJ. Effects of a surgical checklist on decreasing incisional infections following foreign body removal in dogs. Canadian Veterinary Journal, 2019 Jan; 60(1):67-72
Lustgarten, JL, et al. Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure. Data. 2017; 2(1): 5
Lustgarten JL, Visweswaran S, Gopalakrishnan V, Cooper GF. Application of an efficient Bayesian discretization method to biomedical data. BMC Bioinformatics. 2011 Jul 28; 12:309.
Lustgarten, Jonathan Llyle. A Bayesian Rule Generation Framework for 'Omic' Biomedical Data Analysis. Doctoral Dissertation (2009), University of Pittsburgh.
Lustgarten, J.L., Gopalakrishnan, V., Visweswaran, S. Measuring Stability of Feature Selection in Biomedical Datasets. AMIA Annu Symp Proc. 2009; 2009: 406–410
Mowery, D, Harkema, H, Dowling, J, Lustgarten, J.L., Chapman, W. Distinguishing Historical from Current Problems in Clinical Reports—Which Textual Features Help? Proceedings of the BioNLP Workshop, Boulder, CO. 2009, pp. 10-18
Lustgarten, J.L., Visweswaran, S., Hogan, W.R., Gopalakrishnan, V. Knowledge Based Variable Selection for Learning Rules from Proteomic Data. BMC Bioinformatics. 2009; 10(Suppl 9): S16.
Lustgarten, JL. Iterative Evidence-Based Medicine. Veterinary Innovation Summit – Colorado State University, Fort Collins, CO September 28th, 2019
Lustgarten, JL. Common computer-based tools to make your practice better today. Fetch DVM 360, Kansas City, MO August 23rd – 26th 2019
Lustgarten, JL. Don’t be scared of machine learning in veterinary medicine. Fetch DVM 360, Kansas City, MO August 23rd – 26th 2019
Lustgarten, J.L. Make your PIMS sing; set up and modifications to improve performance. Fetch DVM 360, Kansas City, MO August 17th – 20th 2018
Lustgarten J.L. Diagnoses disease faster using patient specific models to help you and your patients. Fetch DVM 360, Kansas City, MO August 17th – 20th 2018
Lustgarten, J.L. Veterinary Innovation Summit, Texas A&M, April 6th – 8th, 2018
Lustgarten, J.L., Okerholm, P., Meyer, E., Practice Management Systems: Using Information to Provide Quality Care and Anticipate Disease. Central Veterinary Conference, Kansas City, MO, August 26th – 29th 2016
Lustgarten, J.L. Private Practice Clinical Veterinary Nutrition. Invited Speaker, ACVN Special Symposium on Private Practice, Denver, CO June 7th 2016
Lustgarten, J.L., Bioinformatics Approaches to Mining Biomarker Datasets Invited Speaker, Special Meeting of the SPORE (Special Projects of Research Excellence) for University of Pittsburgh, University of Pittsburgh Johnstown, PA June 17th, 2009
Lustgarten, J.L., Visweswaran, S., Hogan, W.R., Gopalakrishnan, V. Knowledge Based Variable Selection for Learning Rules from Proteomic Data. Invited Speaker, AMIA Summit on Translational Bioinformatics, March 2009