title: Breast cancer therapy planning - a novel support concept for a sequential decision making problem.
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.
authors.affiliation: Department of Optimization, Fraunhofer Institute for Industrial Mathematics (ITWM), Fraunhofer-Platz 1, 67663, Kaiserslautern, Germany, alexander.scherrer@itwm.fraunhofer.de.
authors.forename: Alexander
authors.initials: A
authors.lastname: Scherrer
authors.forename: Ilka
authors.initials: I
authors.lastname: Schwidde
authors.forename: Andreas
authors.initials: A
authors.lastname: Dinges
authors.forename: Patrick
authors.initials: P
authors.lastname: Rüdiger
authors.forename: Sherko
authors.initials: S
authors.lastname: Kümmel
authors.forename: Karl-Heinz
authors.initials: KH
authors.lastname: Küfer
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000628:therapy*; D003657:Decision Making; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008962:Models, Theoretical
chemical_list: D000970:Antineoplastic Agents