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Donald J Berndt

Biographic Data

ID6072809
NAMEDonald J Berndt
GIVEN NAMESDonald J
FAMILY NAMEBerndt
SIGNATUREBERNDT D J
AFFILIATIONSStephen L. Luther, James A. McCart, Bridget Hahm, Dezon Finch, Philip R. Foulis, William A. Lapcevic, Robert R. Campbell, and Gail Powell-Cope are with the HSR&D Center of Innovation on Disability and Rehabilitation Research, James A. Haley Veterans Hospital, Tampa, FL. Donald J. Berndt is with the University of South Florida College of Business Administration, Tampa. Jay Jarman is with the East Tennessee State University Department of Computing, Johnson City. Ronald I. Shorr is with the North...
ORCID0000-0002-4900-8244
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Freedom of speech or freedom of reach? Strategies for mitigating malicious content in social networks

    Open Access•Saurav Chakraborty, Sandeep Goyal et al.•ARTICLE•Decision Support Systems•2024

  • Improving Identification of Fall-Related Injuries in Ambulatory Care Using Statistical Text Mining

    Stephen L Luther, James A McCart et al.•ARTICLE•American Journal of Public Health•2015•References: 23

    Objectives. We determined whether statistical text mining (STM) can identify fall-related injuries in electronic health record (EHR) documents and the impact on STM models of training on documents from a single or multiple facilities. Methods. We obtained fiscal year 2007 records for Veterans Health Administration (VHA) ambulatory care clinics in the southeastern United States and Puerto Rico, resulting in a total of 26 010 documents for 1652 vet…

No prominent works on this page.

  • Improving Identification of Fall-Related Injuries in Ambulatory Care Using Statistical Text Mining

    Stephen L Luther, James A McCart et al.•ARTICLE•American Journal of Public Health•2015•References: 23

    Objectives. We determined whether statistical text mining (STM) can identify fall-related injuries in electronic health record (EHR) documents and the impact on STM models of training on documents from a single or multiple facilities. Methods. We obtained fiscal year 2007 records for Veterans Health Administration (VHA) ambulatory care clinics in the southeastern United States and Puerto Rico, resulting in a total of 26 010 documents for 1652 vet…

  • Freedom of speech or freedom of reach? Strategies for mitigating malicious content in social networks

    Open Access•Saurav Chakraborty, Sandeep Goyal et al.•ARTICLE•Decision Support Systems•2024

Ambulatory (1 work) · Ambulatory care (1 work) · Chart (1 work) · Computer Science (1 work) · Emergency Medicine (1 work) · Emergency Medicine (1 work) · Family medicine (1 work) · Hate Speech and Cyberbullying Detection (1 work) · Health care (1 work) · Identification (biology) (1 work)

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