TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation

Shorabuddin Syed, Adam Angel, Hafsa Syeda, Carole Jennings, Joseph VanScoy, Mahanazuddin Syed, Melody Greer, Sudeepa Bhattacharyya, Shaymaa Al-Shukri, Meredith Zozus, Fred Prior, Benjamin Tharian

2022

Abstract

Colonoscopy plays a critical role in screening of colorectal carcinomas (CC). Unfortunately, the data related to this procedure are stored in disparate documents, colonoscopy, pathology, and radiology reports respectively. The lack of integrated standardized documentation is impeding accurate reporting of quality metrics and clinical and translational research. Natural language processing (NLP) has been used as an alternative to manual data abstraction. Performance of Machine Learning (ML) based NLP solutions is heavily dependent on the accuracy of annotated corpora. Availability of large volume annotated corpora is limited due to data privacy laws and the cost and effort required. In addition, the manual annotation process is error-prone, making the lack of quality annotated corpora the largest bottleneck in deploying ML solutions. The objective of this study is to identify clinical entities critical to colonoscopy quality, and build a high-quality annotated corpus using domain specific taxonomies following standardized annotation guidelines. The annotated corpus can be used to train ML models for a variety of downstream tasks.

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Paper Citation


in Harvard Style

Syed S., Angel A., Syeda H., Jennings C., VanScoy J., Syed M., Greer M., Bhattacharyya S., Al-Shukri S., Zozus M., Prior F. and Tharian B. (2022). TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF, ISBN 978-989-758-552-4, pages 162-169. DOI: 10.5220/0010876100003123


in Bibtex Style

@conference{healthinf22,
author={Shorabuddin Syed and Adam Angel and Hafsa Syeda and Carole Jennings and Joseph VanScoy and Mahanazuddin Syed and Melody Greer and Sudeepa Bhattacharyya and Shaymaa Al-Shukri and Meredith Zozus and Fred Prior and Benjamin Tharian},
title={TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF,},
year={2022},
pages={162-169},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010876100003123},
isbn={978-989-758-552-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: HEALTHINF,
TI - TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation
SN - 978-989-758-552-4
AU - Syed S.
AU - Angel A.
AU - Syeda H.
AU - Jennings C.
AU - VanScoy J.
AU - Syed M.
AU - Greer M.
AU - Bhattacharyya S.
AU - Al-Shukri S.
AU - Zozus M.
AU - Prior F.
AU - Tharian B.
PY - 2022
SP - 162
EP - 169
DO - 10.5220/0010876100003123