Deakin University
Browse

File(s) under permanent embargo

Understanding Toxicities and Complications of Cancer Treatment: A Data Mining Approach

Version 2 2024-06-02, 00:13
Version 1 2016-02-15, 17:09
conference contribution
posted on 2024-06-02, 00:13 authored by Wei LuoWei Luo
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.

History

Volume

9457

Chapter number

38

Pagination

431-443

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319263496

Language

eng

Publication classification

B1 Book chapter, B Book chapter

Copyright notice

2015, Springer

Extent

57

Editor/Contributor(s)

Pfahringer B, Renz J

Title of proceedings

AI 2015: Advances in Artificial Intelligence

Publisher

Springer

Place of publication

Berlin, Germany

Title of book

AI 2015: Advances in artificial intelligence. 28th Australasian Joint Conference Canberra, ACT, Australia, November 30 - December 4, 2015 Proceedings

Series

Lecture notes in computer science; v.9457

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC