Joseph VanScoy
Researcher
University of Arkansas for Medical Sciences
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Biography and Research Information
OverviewAI-generated summary
Joseph VanScoy's research focuses on the application of advanced computational techniques to clinical data, particularly in the area of colonoscopy and the de-identification of electronic health records. His work involves developing and evaluating neural network models for tasks such as concept compilation and named entity recognition within clinical notes. He has published on models like the h-ANN Model for colonoscopy concept compilation and the DeIDNER Model for de-identifying clinical text. VanScoy has also contributed to the development of the TAX-Corpus, a dataset for evaluating colonoscopy annotations. His scholarship metrics include an h-index of 2 with 19 total citations across 3 publications. He collaborates with researchers from the University of Arkansas for Medical Sciences and Arkansas State University, including Fred Prior and Sudeepa Bhattacharyya.
Metrics
- h-index: 2
- Publications: 3
- Citations: 19
Selected Publications
- TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation (2022) DOI
- DeIDNER Model: A Neural Network Named Entity Recognition Model for Use in the De-identification of Clinical Notes (2022) DOI
- The h-ANN Model: Comprehensive Colonoscopy Concept Compilation using Combined Contextual Embeddings (2022) DOI
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