H2D: Hierarchical Heterogeneous Graph Learning Framework for Drug-Drug Interaction Prediction.
Ran Zhang|Xuezhi Wang|Sheng Wang|Kunpeng Liu|Yuanchun Zhou|Pengfei Wang
| Anthology ID: | DBLP:conf/cikm/00080W0Z024 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4283-4287 |
| URL: | https://doi.org/10.1145/3627673.3679936 |
| DOI: | https://doi.org/10.1145/3627673.3679936 |
| DBLP: | conf/cikm/00080W0Z024 |
| BibTeX: |
@inproceedings{zhang-2024-h2d,
author = {Ran Zhang and
Xuezhi Wang and
Sheng Wang and
Kunpeng Liu and
Yuanchun Zhou and
Pengfei Wang},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{H2D: Hierarchical Heterogeneous Graph Learning Framework for Drug-Drug Interaction Prediction}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {4283--4287},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3679936},
doi = {https://doi.org/10.1145/3627673.3679936}
}