Intelligent breast cancer predictive system

Clarence Augustine Tee, P. L.N.G. Rao

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents the breast cancer clinical decision support system prototype using our designed data mining techniques and modeling algorithms. We explore previous research works in this area and address the limitations in those systems vis-à-vis ours. Our system and algorithms can address those shortcomings and demonstrate its novelty in clinical comparative studies with real breast cancer patients. Key features of our demonstrator are the ability to predict survival rate (5 years post-diagnosis) of breast cancer patients, predict the tumor growth stage and estimate the survivability period (post-diagnosis) for the breast cancer patient. Our demo system could analyze the weightage influence of each breast cancer patient's medical variables. The demonstrator would provide similarity case reports with detailed histopathology medical conditions reports. The demo system would allow users to store, extract and edit the patients' database virtually and securely. Our demo system supports database and users' accounts confidentiality via secure user names and passwords logins.

Original languageEnglish
Pages (from-to)1489-1493
Number of pages5
JournalJournal of Medical Imaging and Health Informatics
Volume6
Issue number6
DOIs
Publication statusPublished - 10-2016

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Health Informatics

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