- Featured in Women in AMIA, Podcast series, https://podcasts.apple.com/us/podcast/women-in-amia-episode-7-dr-gondy-leroys-career-path/id1453198463?i=1000446761365 , August 2019
- Eller Professorship Award, University of Arizona, 2017 – current.
- AIS Women’s Network Service Award, 2018.
- Eller College of Management, Dean’s Research Award, 2017.
- Recognition “Outstanding College” during my terms as Co-Chair of the Association for Information Systems – Women’s Network, 2018.
- Recognition “Outstanding College” during my terms as Co-Chair of the Association for Information Systems – Women’s Network, 2017.
- Eller Fellow Award, University of Arizona, 2016 – 2017.
Professor of MIS
McClelland Hall 430W
1130 E. Helen St.
P.O. Box 210108
Tucson, Arizona 85721-0108
Areas of Expertise
- Natural language processing, text mining and text analytics
- Search engines, information retrieval/extraction and understanding by consumers
- Medical and biomedical informatics
- Human computer interaction and user studies
PhD, The University of Arizona, 2003
Gondy Leroy joined the Eller College of Management in 2013. Before coming to Eller, she taught at Claremont Graduate College, which she joined after earning her PhD in Management Information Systems from the University of Arizona in 2003. Her areas of expertise include natural language processing, text mining, text analytics, search engines, information retrieval and extraction and understanding by consumers, medical and biomedical informatics and human computer interaction and user studies. She is a member of the Association for Information Systems (AIS), the Eller College Diversity and Inclusion Task Force and a senior member of the Institute of Electrical and Electronics Engineers.
- MIS 545 Data Mining for Business Intelligence
- G. Leroy and D. Kauchak, "A Comparison of Text versus Audio for Information Comprehension with Future Uses for Smart Speakers", JAMIA Open, 2 (2), July 2019, Pages 254–260, 2019. [DOI: 10.1093/jamiaopen/ooz011]
- P. Harber and G. Leroy, "Insights from Twitter about Public Perceptions of Asthma, COPD, and Exposures", Journal of Occupational and Environmental Medicine (JOEM), Jun;61(6):484-490. [DOI: 10.1097/JOM.0000000000001590].
- P. Mukherjee, G. Leroy and D. Kauchak, "Using Lexical Chains to Identify Text Difficulty: A Corpus Statistics and Classification Study", IEEE Journal of Biomedical and Health Informatics. [Accepted].
- G. Leroy, Y. Gu, S. Pettyrgrove, M.K. Galindo, A. Arora, M. Kurzius-Spencer, "Automated Extraction of Diagnostic Criteria from Electronic Health Recordes for Autism Spectrum Disorders: Development, Evaluation and Case Study", Journal of Medical Internet Research (JMIR), 20, 11, 2018. [DOI: 10.2196/10497]
- N. Kloehn, G. Leroy, D. Kauchak, Y. Gu, S. Colina, N.P. Yuan, D.Revere, " Improving Consumer Understanding of Medical Text: Development and Validation of a New SubSimplify Algorithm to Automatically Generate Term Explanations in English and Spanish”, Journal of Medical Internet Research (JMIR), 20, 8, 2018.[DOI: 10.2196/10779]
- M. Wimble and G. Leroy, "Health Information Technology: Promise and Progress", Health Systems, June 2018. [DOI: 10.1080/20476965.2018.1473944][Peer reviewed editorial]
- P. Mukherjee, G. Leroy, D. Kauchak, S. Rajnarayanan, D. Diaz, N. Yuan, T. Pritchard, and S. Colina, "NegAIT: A New Parser for Medical Text Simplification Using Morphological, Sentential and Double Negation", Journal of Biomedical Informatics, 69, 55-62 2017. [NegAIT Source code: https://github.com/kloehnen/NegAIT, http://nlp.lab.arizona.edu/content/resources]
- D. Kauchak, G. Leroy and A. Hogue, "Measuring Text Difficulty Using Parse-Tree Frequency", Journal of the Association for Information Science and Technology (JASIST), 68, 9, 2017.
- P. Harber and G. Leroy, "Feasibility and Utility of Lexical Analysis for Occupational Health Text", Journal of Occupational and Environmental Medicine (JOEM), June, 59, 6, 578-587, 2017. [doi: 10.1097/JOM.0000000000001035]
- P. Harber and G. Leroy, "Social Media Use for Occupational Lung Disease", Current Opinion in Allergy & Clinical Immunology, 17(2), 72-77, 2017.
- D. Kauchak and G. Leroy, “Moving Beyond Readability Metrics for Simplifying Health-related Text”, IEEE IT Professional, 8(3), 45-51, 2016.
- G. Leroy, D. Kauchak and A. Hogue, “Effects on Text Simplification: Evaluation of Splitting up Noun Phrases”, Journal of Health Communication, 21 (Supp1), 18-26, 2016.[doi: 10.1080/10810730.2015.1131775.]
- P. Harber and G. Leroy, "Assessing Work-Asthma Interaction with Amazon Mechanical Turk", Journal of Occupational and Environmental Medicine (JOEM), April, 57 (4), 381-385, 2015.
- C.-H. Ku and G. Leroy, "A Decision Support System: Automated Crime Report Analysis and Classification for e-Government", Government Information Quarterly, 31 (4), 2014.
- G. Leroy and D. Kauchak, "The Effect of Word Familiarity on Actual and Perceived Text Difficulty", Journal of the American Medical Informatics Association (JAMIA), 21, e1, 2014. [doi:10.1136/amiajnl-2013-002172 ]
- M. Kwak, G. Leroy, J.D. Martinez, and J. Harwell, "Development and Evaluation of a Biomedical Search Engine using a Predicate-based Vector Space Model", Journal of Biomedical Informatics, 15, 7, e144, 2013.[doi: 10.1016/j.jbi.2013.07.006]
- G. Leroy, J.E. Endicott, D. Kauchak, O. Mouradi, and M. Just, "User Evaluation of the Effects of a Text Simplification Algorithm using Term Familiarity on Perception, Understanding, Learning and Information Retention,” Journal of Medical Internet Research (JMIR), 15(7):e144, 2013.
- G. Leroy, D. Kauchak, and O. Mouradi, “A User-study Measuring the Effects of Lexical Simplification and Coherence Enhancement on Perceived and Actual Text Difficulty”, International Journal of Medical Informatics, 82, 8, 717-730, 2013.
Invited Talks and Presentations
- “Generating Data from Text in EHR (with Autism Spectrum Disorders as an Example)”, Department of Infectious Diseases, College of Medicine, University of Arizona, April 2020.
- “Information Technology to Support Diagnosing Autism Spectrum Disorders,” The Autism and Developmental Disabilities Monitoring (ADDM) Network , January 22, 2020.
- “Promise and opportunity for natural language processing to generate new data from EHR: Autism Spectrum Disorders Example, “Department of Epidemiology and Biostatistics, College of Public Health, Department of Epidemiology and Biostatistics, College of Public Health, November 20, University of Arizona.
- “Data sets without ground truth: Creating data from behavioral descriptions in text”, Women in Data Science, Tucson Edition, April 4, 2019.
- “Automating diagnostic criteria annotation and case decisions for autism spectrum disorders based on the free text in EHR”, Clinical Informatics Grand Rounds, College of Medicine – Phoenix, March 20, 2019.