Understanding toxicities and complications of cancer treatment: a data mining approach

Dang Nguyen, Wei Luo, Dinh Phung, Svetha Venkatesh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

3 Citations (Scopus)


Cancer remains a major challenge in modern medicine. Increasing prevalence of cancer, particularly in developing countries, demands better understanding of the effectiveness and adverse consequences of different cancer treatment regimes in real patient population. Current understanding of cancer treatment toxicities is often derived from either “clean” patient cohorts or coarse population statistics. It is difficult to get up-to-date and local assessment of treatment toxicities for specific cancer centres. In this paper, we applied an Apriori-based method for discovering toxicity progression patterns in the form of temporal association rules. Our experiments show the effectiveness of the proposed method in discovering major toxicity patterns in comparison with the pairwise association analysis. Our method is applicable for most cancer centres with even rudimentary electronic medical records and has the potential to provide real-time surveillance and quality assurance in cancer care.

Original languageEnglish
Title of host publicationAI 2015: Advances in Artificial Intelligence
Subtitle of host publication28th Australasian Joint Conference Canberra, ACT, Australia, November 30 – December 4, 2015 Proceedings
EditorsBernhard Pfahringer, Jochen Renz
Place of PublicationCham Switzerland
Number of pages13
ISBN (Electronic)9783319263502
ISBN (Print)9783319263496
Publication statusPublished - 2015
Externally publishedYes
EventAustralasian Joint Conference on Artificial Intelligence 2015 - Canberra, Australia
Duration: 30 Nov 20154 Dec 2015
Conference number: 28th
https://link.springer.com/book/10.1007/978-3-319-26350-2 (Proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceAustralasian Joint Conference on Artificial Intelligence 2015
Abbreviated titleAI 2015
Internet address

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