Shyam Visweswaran
Associate Professor
Biomedical Informatics
University of Pittsburgh
France
Biography
I am a tenured Associate Professor of Biomedical Informatics with training in informatics, artificial intelligence and clinical neurology. My research is focused on the application of artificial intelligence and machine learning to problems in the Learning Health System (LHS) that include: development of a learning Electronic Medical Record (LEMR) system, precision medicine and personalized modeling, data mining and causal discovery from biomedical data, research data warehousing for clinical, translational, and informatics research, and automated visual analytics. The Vis Lab is in the Department of Biomedical Informatics at the University of Pittsburgh, and is a core faculty laboratory in the Biomedical Informatics Training Program and the Intelligent Systems Program at the University of Pittsburgh.
Research Interest
Application of artificial intelligence, machine learning, data mining and Bayesian methods to problems in clinical medicine and bioinformatics, data mining of biomedical data, patient-specific predictive modeling, medical anomaly detection, decision support systems, personalized medicine and genomic medicine.
Publications
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King AJ, Hochheiser, Visweswaran S, Clermont G, Cooper GF. Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR. Proceedings of the AMIA Joint Summit on Translational Science (2017).
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Lustgarten JL, Balasubramanian JB, Visweswaran S, Gopalakrishnan V, Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure. 2017 Mar;2(1). pii: 5. doi: 10.3390/data2010005. Epub 2017 Jan 18. PMID: 28331847 PMCID: PMC5358670 DOI: 10.3390/data2010005
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King, A. J., Hochheiser, H., Visweswaran, S., Clermont, G., & Cooper, G. F. (2017). Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR. AMIA Summits on Translational Science Proceedings, 2017, 512–521. Sergio M. Castro, Eugene Tseytlin, Olga Medvedeva, Kevin Mitchell, Shyam Visweswaran, Tanja Bekhuis, Rebecca S. Jacobson, Automated annotation and classification of BI-RADS assessment from radiology reports, Journal of Biomedical Informatics, Volume 69, May 2017, Pages 177-187, ISSN 1532-0464, https://doi.org/10.1016/j.jbi.2017.04.011. (http://www.sciencedirect.com/science/article/pii/S1532046417300813)
