Multiple detection modalities and disease natural history of breast cancer

Tony Hsiu Hsi Chen, Ming-Fang Yen, Grace Hui Min Wu, Li-Sheng Chen, Yueh Hsia Chiu

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

2 Citations (Scopus)


Multiple detection modalities have increasingly gained attention in population-based screening. However, the disease natural history and its efficacy have been barely addressed. We reviewed a series of articles addressing multiple detection modalities including mammography, ultrasound and magnetic resonance image between 1995 and 2005. A stochastic model was developed to estimate transition parameters pertaining to the disease natural history defined by multiple detection modalities. The effectiveness of the combination of ultrasound or magnetic resonance image (MRI) with mammography was projected using a series of computer simulation models. The results indicated that multiple detection modalities may lead to reduced mortality. However, the benefit and the selection of detection modalities are affected by biological factors including age, breast tissue type and histological type. In addition, other social factors may also affect the utilization of multiple detection modalities.

Original languageEnglish
Title of host publicationMEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics
Subtitle of host publicationBuilding Sustainable Health Systems
PublisherIOS Press
Number of pages4
ISBN (Print)9781586037741
Publication statusPublished - 2007
Externally publishedYes
Event12th World Congress on Medical Informatics, MEDINFO 2007 - Brisbane, QLD, Australia
Duration: Aug 20 2007Aug 24 2007

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Other12th World Congress on Medical Informatics, MEDINFO 2007
CityBrisbane, QLD


  • breast cancer
  • modality
  • screening
  • stochastic model

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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