Jake Erwin

Researcher

University of Arkansas for Medical Sciences

grad_student

1 h-index 1 pubs 6 cited

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Biography and Research Information

OverviewAI-generated summary

Jake Erwin's research focuses on the application of advanced computational methods to de-identify clinical notes. His work has resulted in the development of the DeIDNER model, a neural network designed for named entity recognition in this context. This model aims to enhance the privacy and security of patient data within clinical documentation. Erwin has collaborated with researchers including Fred Prior, Kevin W. Sexton, Farhan Kawsar, and Joseph VanScoy at the University of Arkansas for Medical Sciences. His scholarly output includes one publication with a total of six citations, and he holds an h-index of 1.

Metrics

  • h-index: 1
  • Publications: 1
  • Citations: 6

Selected Publications

  • DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes (2022) DOI

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