We present a prototype tool to visualize and review the result of using NLP techniques to extract boolean variables from clinical text. Our tool combines multiple visualizations to help the users understand these results and make any necessary corrections to the models, thus forming a feedback loop and helping improve the accuracy of the NLP models. More details about the project are available [here](http:// trivedigaurav.com/blog/clinical-text-analysis-using-interactive-natural-language-processing/).
Docker: https://github.com/NLPReViz/nlpreviz-docker | Dockerfile
Interface: http://github.com/NLPReViz/emr-vis-web | Zip | Tar
NLP Server: http://github.com/NLPReViz/emr-nlp-server | Zip | Tar
Gaurav Trivedi, Phuong Pham, Wendy W Chapman, Rebecca Hwa, Janyce Wiebe, Harry Hochheiser; NLPReViz: an interactive tool for natural language processing on clinical text, Journal of the American Medical Informatics Association, Volume 25, Issue 1, 1 January 2018, Pages 81–87, DOI: 10.1093/jamia/ocx070.
@article{doi:10.1093/jamia/ocx070,
author = {Trivedi, Gaurav and Pham, Phuong and Chapman, Wendy W and Hwa, Rebecca and Wiebe, Janyce and Hochheiser, Harry},
title = { {N}{L}{P}{R}e{V}iz: an interactive tool for natural language processing on clinical text},
journal = {Journal of the American Medical Informatics Association},
volume = {25},
number = {1},
pages = {81-87},
year = {2018},
doi = {10.1093/jamia/ocx070},
URL = {http://dx.doi.org/10.1093/jamia/ocx070}
}
Concept: Gaurav Trivedi. 2015. Clinical Text Analysis Using Interactive Natural Language Processing. In Proceedings of the 20th International Conference on Intelligent User Interfaces Companion (IUI Companion ’15). ACM, New York, NY, USA, 113-116. DOI: 10.1145/2732158.2732162
@inproceedings{Trivedi2015,
author = {Trivedi, Gaurav},
title = {Clinical Text Analysis Using Interactive Natural Language Processing},
booktitle = {Proceedings of the 20th International Conference on Intelligent User Interfaces Companion},
series = {IUI Companion '15},
year = {2015},
isbn = {978-1-4503-3308-5},
location = {Atlanta, Georgia, USA},
pages = {113--116},
numpages = {4},
url = {http://doi.acm.org/10.1145/2732158.2732162},
doi = {10.1145/2732158.2732162},
acmid = {2732162},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {electronic medical records, interactive machine learning, visualization},
}
Initial Design and Evaluation: Gaurav Trivedi, Phuong Pham, Wendy Chapman, Rebecca Hwa, Janyce Wiebe, Harry Hochheiser. 2015. An Interactive Tool for Natural Language Processing on Clinical Text. Presented at 4th Workshop on Visual Text Analytics (IUI TextVis 2015), Atlanta. Available: http://vialab.science.uoit.ca/textvis2015/papers/Trivedi-textvis2015.pdf
@InProceedings{Trivedi2015TextVis,
author = {Trivedi, Gaurav and Pham, Phuong and Chapman, Wendy and Hwa, Rebecca and Wiebe, Janyce and Hochheiser, Harry},
title = {An Interactive Tool for Natural Language Processing on Clinical Text},
booktitle = {4th Workshop on Visual Text Analytics (IUI TextVis 2015)},
year = 2015,
address = {Atlanta},
month = {Mar},
url = {http://vialab.science.uoit.ca/textvis2015/papers/Trivedi-textvis2015.pdf}
}
Jaromír Šavelka, Gaurav Trivedi, and Kevin Ashley. 2015. Applying an Interactive Machine Learning Approach to Statutory Analysis. In Proceedings of the 28th International Conference on Legal Knowledge and Information Systems (JURIX ’15). Braga, Portugal – Awarded the Best Student Paper.