IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v18y2015i3p389-405.html
   My bibliography  Save this article

Breast cancer therapy planning – a novel support concept for a sequential decision making problem

Author

Listed:
  • Alexander Scherrer
  • Ilka Schwidde
  • Andreas Dinges
  • Patrick Rüdiger
  • Sherko Kümmel
  • Karl-Heinz Küfer

Abstract

Breast cancer is the most common carcinosis with the largest number of mortalities in women. Its therapy comprises a wide spectrum of different treatment modalities a breast oncologist decides about for the individual patient case. These decisions happen according to medical guide lines, current scientific publications and experiences acquired in former cases. Clinical decision making therefore involves the time-consuming search for possible therapy options and their thorough testing for applicability to the current patient case.This research work addresses breast cancer therapy planning as a multi-criteria sequential decision making problem. The approach is based on a data model for patient cases with therapy descriptions and a mathematical notion for therapeutic relevance of medical information. This formulation allows for a novel decision support concept, which targets at eliminating observed weaknesses in clinical routine of breast cancer therapy planning. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Alexander Scherrer & Ilka Schwidde & Andreas Dinges & Patrick Rüdiger & Sherko Kümmel & Karl-Heinz Küfer, 2015. "Breast cancer therapy planning – a novel support concept for a sequential decision making problem," Health Care Management Science, Springer, vol. 18(3), pages 389-405, September.
    • Handle: RePEc:kap:hcarem:v:18:y:2015:i:3:p:389-405
    DOI: 10.1007/s10729-014-9302-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10729-014-9302-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10729-014-9302-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nazila Bazrafshan & M. M. Lotfi, 2020. "A finite-horizon Markov decision process model for cancer chemotherapy treatment planning: an application to sequential treatment decision making in clinical trials," Annals of Operations Research, Springer, vol. 295(1), pages 483-502, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:hcarem:v:18:y:2015:i:3:p:389-405. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.