ClinicalRisk: A New Therapy-related Clinical Trial Dataset for Predicting Trial Status and Failure Reasons.
Junyu Luo|Zhi Qiao|Lucas Glass|Cao Xiao|Fenglong Ma
| Anthology ID: | DBLP:conf/cikm/Luo0GXM23 |
|---|---|
| Volume: | Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023 |
| Year: | 2023 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 5356-5360 |
| URL: | https://doi.org/10.1145/3583780.3615113 |
| DOI: | https://doi.org/10.1145/3583780.3615113 |
| DBLP: | conf/cikm/Luo0GXM23 |
| BibTeX: |
@inproceedings{luo-2023-clinicalrisk,
author = {Junyu Luo and
Zhi Qiao and
Lucas Glass and
Cao Xiao and
Fenglong Ma},
editor = {Ingo Frommholz and
Frank Hopfgartner and
Mark Lee and
Michael P. Oakes and
Mounia Lalmas-Roelleke and
Min Zhang and
Rodrygo L. T. Santos},
title = {{ClinicalRisk: A New Therapy-related Clinical Trial Dataset for Predicting Trial Status and Failure Reasons}},
booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}},
pages = {5356--5360},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3583780.3615113},
doi = {https://doi.org/10.1145/3583780.3615113}
}