Dezon K. Finch, Ph.D.

Affiliations: 
2012 Information Systems and Decision Sciences University of South Florida, Tampa, FL, United States 
Area:
Information Science, Computer Science
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"Dezon Finch"

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Donald Berndt grad student 2012 University of South Florida
 (TagLine: Information Extraction for Semi-Structured Text Elements In Medical Progress Notes.)
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Publications

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Luther SL, Thomason SS, Sabharwal S, et al. (2023) Machine learning to develop a predictive model of pressure injury in persons with spinal cord injury. Spinal Cord
Luther SL, Finch DK, Bouayad L, et al. (2021) Measuring pain care quality in the Veterans Health Administration primary care setting. Pain
Luther SL, Thomason SS, Sabharwal S, et al. (2017) Leveraging Electronic Health Care Record Information to Measure Pressure Ulcer Risk in Veterans With Spinal Cord Injury: A Longitudinal Study Protocol. Jmir Research Protocols. 6: e3
Luther SL, McCart JA, Berndt DJ, et al. (2015) Improving identification of fall-related injuries in ambulatory care using statistical text mining. American Journal of Public Health. 105: 1168-73
Berndt DJ, McCart JA, Finch DK, et al. (2015) A Case Study of Data Quality in Text Mining Clinical Progress Notes Acm Transactions On Management Information Systems. 6: 1-21
Finch DK, McCart JA, Luther SL. (2014) TagLine: Information Extraction for Semi-Structured Text in Medical Progress Notes. Amia ... Annual Symposium Proceedings / Amia Symposium. Amia Symposium. 2014: 534-43
Dillahunt-Aspillaga C, Finch D, Massengale J, et al. (2014) Using information from the electronic health record to improve measurement of unemployment in service members and veterans with mTBI and post-deployment stress. Plos One. 9: e115873
Finch D, Dillahunt-Aspillaga C, Luther S, et al. (2014) Using the Electronic Health Record to Improve Measurement of Unemployment in Veterans With TBI Archives of Physical Medicine and Rehabilitation. 95: e53
McCart JA, Berndt DJ, Jarman J, et al. (2013) Finding falls in ambulatory care clinical documents using statistical text mining. Journal of the American Medical Informatics Association : Jamia. 20: 906-14
McCart JA, Finch DK, Jarman J, et al. (2012) Using ensemble models to classify the sentiment expressed in suicide notes. Biomedical Informatics Insights. 5: 77-85
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