1. Kushima, M., Honda, Y., Le, H.H., Yamazaki, T., Araki, K., Yokota, H.: Visualization and analysis of variants in catheter ablation’s clinical pathways from electronic medical record logs. In: Lecture Notes in Engineering and Computer Science: Proceedings of the International MultiConference of Engineers and Computer Scientists, 14–16 March 2018, Hong Kong, pp. 271–275 (2018)
2. Le, H.H., Edman, H., Honda, Y., Kushima, M., Yamazaki, T., Araki, K., Yokota, H.: Fast generation of clinical pathways including time intervals in sequential pattern mining on electronic medical record systems. In: The 2017 International Conference on Computational Science and Computational Intelligence, Proceeding of the fourth International Conference on Computational Science and Computational Intelligence (CSCI 2017), December 2017
3. Honda, Y., Kushima, M., Yamazaki, T., Araki, K., Yokota, H.: Detection and visualization of variants in typical medical treatment sequences. In: International Workshop on Data Management and Analytics for Medicine and Healthcare, Proceeding of the third International Workshop on Data Management and Analytics for Medicine and Healthcare (DMAH 2017), in Conjunction with the 43rd International Conference on Very Large Database (VLDB 2017), pp. 88–101, September 2017
4. Pei, J., Han, J., Mortazavi-Asl, B., Pinto, H., Chen, Q., Dayal, U., Hsu, M.: PrefixSpan: mining sequential patterns efficiently by prefix-projected pattern growth. In: Proceedings of 2001 International Conference on Data Engineering, pp. 215–224 (2001)
5. Achar, A., Laxman, S., Raajay, V., Sastry, P.S.: Discovering general partial orders from event streams. Technical report.
arXiv:0902.1227v2
[cs.AI].
http://arxiv.org