Deep Learning Approach to Parse Eligibility Criteria in Dietary Supplements Clinical Trials Following OMOP Common Data Model. Bompelli, A., Li, J., Xu, Y., Wang, N., Wang, Y., Adam, T., He, Z., & Zhang, R. AMIA Annu Symp Proc, 2020:243-252, 2020.
Paper doi bibtex @article{RN179,
author = {Bompelli, A. and Li, J. and Xu, Y. and Wang, N. and Wang, Y. and Adam, T. and He, Z. and Zhang, R.},
title = {Deep Learning Approach to Parse Eligibility Criteria in Dietary Supplements Clinical Trials Following OMOP Common Data Model},
journal = {AMIA Annu Symp Proc},
volume = {2020},
pages = {243-252},
ISSN = {1942-597X (Electronic)
1559-4076 (Linking)},
DOI = {056_3415023 [pii]},
url = {https://www.ncbi.nlm.nih.gov/pubmed/33936396
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075443/pdf/056_3415023.pdf},
year = {2020},
type = {Journal Article}
}
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