Cancer Treatment Classification with Electronic Medical Health Records (Student Abstract)

Jiaming Zeng; Imon Banerjee; Michael Gensheimer; Daniel Rubin

doi:10.1609/aaai.v34i10.7263

Cancer Treatment Classification with Electronic Medical Health Records (Student Abstract)

Authors

Jiaming Zeng Stanford University
Imon Banerjee Emory University
Michael Gensheimer Stanford University
Daniel Rubin Stanford University

DOI:

https://doi.org/10.1609/aaai.v34i10.7263

Abstract

We built a natural language processing (NLP) language model that can be used to extract cancer treatment information using structured and unstructured electronic medical records (EMR). Our work appears to be the first that combines EMR and NLP for treatment identification.

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Published

2020-04-03

How to Cite

Zeng, J., Banerjee, I., Gensheimer, M., & Rubin, D. (2020). Cancer Treatment Classification with Electronic Medical Health Records (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 34(10), 13981-13982. https://doi.org/10.1609/aaai.v34i10.7263