Rohit Kate

Associate Professor, Computer Science

Dr. Kate's research focus is on applying machine learning techniques to do predictive analytics for medical applications as well as on applying natural language processing techniques to automate analysis of biomedical and clinical text.

Education

PhD Computer Science, The University of Texas at Austin, 2007
MS Computer Science, The University of Texas at Austin, 2002
B.Tech., Computer Science and Engineering, Indian Institute of Technology, Delhi, 2000

Research Interests

Natural Language Processing
Machine Learning
Biomedical Informatics
Artificial Intelligence

Publications

Google Scholar link

Rohit J. Kate. Clinical Term Normalization Using Learned Edit Patterns and Subconcept Matching: System Development and Evaluation, JMIR Medical Informatics, Volume 9, Number 1, e23104, January 2021.
Rohit J. Kate. Automatic Full Conversion of Clinical Terms into SNOMED CT Concepts, Journal of Biomedical Informatics, Volume 111, 103585, November 2020.
Rohit J. Kate, Noah Pearce, Debesh Mazumdar and Vani Nilakantan. A Continual Prediction Model for Inpatient Acute Kidney Injury. Computers in Biology and Medicine, Volume 116, 103580, January 2020.
Omid Ghiasvand and Rohit J. Kate. Learning for Clinical Named Entity Recognition without Manual Annotations. Informatics in Medicine Unlocked, Volume 13, 122-127, October 2018.
Rohit J. Kate, Sarah Rubatt, Chukuka S. Enwemeka and Wendy E. Huddleston. Optimal Laser Phototherapy Parameters for Pain Relief. Photomedicine and Laser Surgery, Volume 36, Number 7, 354-362, July 2018.
Elham Sagheb Hossein Pour and Rohit J. Kate. Stage-Specific Survivability Prediction Models across Different Cancer Types. In Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium, pp. 1404-1412, Washington, DC, November 2017.
Rohit J. Kate and Ramya Nadig. Stage-Specific Predictive Models for Breast Cancer Survibability. International Journal of Medical Informatics, Volume 97, 304-311, January 2017.
Rohit J. Kate, Ruth M. Perez, Debesh Mazumdar, Kalyan S. Pasupathy and Vani Nilakantan. Prediction and Detection Models for Acute Kidney Injury in Hospitalized Older Adults. BMC Medical Informatics and Decision Making, 2016, 16:39.
Rohit J. Kate, Ann M. Swartz, Whitney A. Welch and Scott J. Strath. Comparative Evaluation of Features and Techniques for Identifying Activity Type and Estimating Energy Cost from Accelerometer Data. Physiological Measurement, Volume 37, Number 3, 360-379, March 2016.
Rohit J. Kate. Using Dynamic Time Warping Distances as Features for Improved Time Series Classification. Data Mining and Knowledge Discovery, Volume 30, Issue 2, 283-312, March 2016.
Rohit J. Kate. Normalizing Clinical Terms Using Learned Edit Distance Patterns. Journal of the American Medical Informatics Association, Volume 23, Issue 2, 380-386, March 2016.
Scott J. Strath, Rohit J. Kate, Kevin G. Keenan, Whitney A. Welch and Ann M. Swartz. Ngram Time Series Model to Predict Activity Type and Energy Cost from Wrist, Hip and Ankle Accelerometers: Implications of Age. Physiological Measurement, Volume 36, Number 11, 2335-2351, November 2015.
Rohit J. Kate. Towards Converting Clinical Phrases into SNOMED CT Expressions. Biomedical Informatics Insights 2013:6 (Suppl. 1) 29-37.
Rohit J. Kate. Unsupervised Grammar Induction of Clinical Report Sublanguage. Journal of Biomedical Semantics 2012, 3(Suppl 3):S4.

Please see the complete list at: https://sites.uwm.edu/katerj/publications/