Biography and Research Information
OverviewAI-generated summary
Jake Erwin's research focuses on the application of artificial intelligence in healthcare, specifically in the de-identification of clinical notes. His work involves developing and utilizing neural network models for named entity recognition (NER) to protect patient privacy. He has published on the "DeIDNER Model," a neural network designed for this purpose.
Erwin has collaborated with researchers at the University of Arkansas for Medical Sciences, including Melody Greer, Fred Prior, Kevin W. Sexton, and Farhan Kawsar, on shared publications. His scholarly output includes one publication with a total of six citations and an h-index of 1. He is noted as recently active in his research endeavors.
Metrics
- h-index: 1
- Publications: 1
- Citations: 6
Selected Publications
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DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes (2022)
Collaboration Network
Top Collaborators
Mahanazuddin Syed
University of Arkansas for Medical Sciences (US)
1 shared publication
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Kevin W. Sexton
University of Arkansas for Medical Sciences
1 shared publication
In database
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Melody Greer
University of Arkansas for Medical Sciences (US)
1 shared publication
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Shorabuddin Syed
University of Arkansas for Medical Sciences (US)
1 shared publication
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Joseph VanScoy
University of Arkansas for Medical Sciences
1 shared publication
In database
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Farhan Kawsar
University of Arkansas for Medical Sciences
1 shared publication
In database
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Evan Olson
University of Arkansas for Medical Sciences (US)
1 shared publication
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Karan Patel
University of Arkansas for Medical Sciences (US)
1 shared publication
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Sudeepa Bhattacharyya
Arkansas Biosciences Institute
1 shared publication
In database
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Meredith Zozus
The University of Texas Health Science Center at San Antonio (US)
1 shared publication
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Fred Prior
University of Arkansas for Medical Sciences
1 shared publication
In database
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes
Similar Researchers
Based on overlapping research topics
Joseph VanScoy
University of Arkansas for Medical Sciences
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University of Arkansas for Medical Sciences
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Susan Gauch
University of Arkansas at Fayetteville
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University of Arkansas at Fayetteville
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Arkansas Tech University
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Fu Weiping
University of Arkansas at Fayetteville
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