Indirect Association Rules Mining in Clinical Texts-Reference-Cited by-同舟云学术

Indirect Association Rules Mining in Clinical Texts

Published:2018 Issue: Volume: Page:36-47
ISSN:0302-9743
Container-title:Artificial Intelligence: Methodology, Systems, and Applications
language:
Short-container-title:

Author:

Boytcheva Svetla^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-99344-7_4

Reference27 articles.

1. Lecture Notes in Computer Science;Z Abdullah,2014

2. Agrawal, R., Srikant, R., et al.: Fast algorithms for mining association rules. In: Proceedings of the 20th International Conference very large data bases, VLDB. vol. 1215, pp. 487–499 (1994)

3. Boytcheva, S., Angelova, G., Angelov, Z., Tcharaktchiev, D.: Integrating data analysis tools for better treatment of diabetic patients. CEUR Workshop Proc. 2022, 229–236 (2017)

4. Boytcheva, S., Nikolova, I., Angelova, G.: Mining association rules from clinical narratives. In: Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pp. 130–138 (2017)

5. Boytcheva, S., Nikolova, I., Angelova, G., Angelov, Z.: Identification of risk factors in clinical texts through association rules. In: Proceedings of the Biomedical NLP Workshop associated with RANLP, pp. 64–72 (2017)

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Associative patterns in health data: exploring new techniques;Health and Technology;2022-01-21

2. Data structuring of electronic health records: a systematic review;Health and Technology;2021-10-29

3. Unsupervised Approaches for Textual Semantic Annotation, A Survey;ACM Computing Surveys;2020-07-31

4. Population-based metaheuristics for Association Rule Text Mining;Proceedings of the 2020 4th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence;2020-03-21