2026-08-06T10:10:39Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:21360 2024-10-28T08:50:38Z ddc:004 open_access

Helping Cancer Patients to Choose the Best Treatment: Towards Automated Data-Driven and Personalized Information Presentation of Cancer Treatment Options Krahmer, Emiel Clouth, Felix Hommes, Saar Vromans, Ruben Pauws, Steffen Vermunt, Jeroen van de Poll-Franse, Lonneke Verbeek, Xander Oncology Data-driven shared decision making Latent class analysis Risk communication Narratives Personalization When a person is diagnosed with cancer, difficult decisions about treatments need to be made. In this chapter, we describe an interdisciplinary research project which aims to automatically generate personalized descriptions of treatment options for patients. We relied on two large databases provided by the Netherlands Comprehensive Cancer Organisation (IKNL): The Netherlands Cancer Registry and the PROFILES dataset. Combining these datasets allowed us to extract personalized information about treatment options for different types of cancer. In a next step we provided personalized context to these numbers, both in verbal statements and in narratives, with the aim to facilitate shared decision making about treatments. We discuss strengths and limitations of our approach, illustrate how it generalizes to other health domains, and reflect on the overall research project. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Emiel Krahmer and Felix Clouth and Saar Hommes and Ruben Vromans and Steffen Pauws and Jeroen Vermunt and Lonneke van de Poll-Franse and Xander Verbeek 2024 Is Part Of OASIcs, Volume 124, Commit2Data (2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.Commit2Data.3 urn:nbn:de:0030-drops-213609 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Commit2Data.3 eng https://creativecommons.org/licenses/by/4.0/legalcode