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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,Lonneke
; 
Verbeek,Xander
Abstract
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.
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Date
2024
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Schloss Dagstuhl - Leibniz fuer Informatik
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Tilburg University Research Output Collection
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Helping_Cancer_Patients_to_Choose_the_Best_Treatment.pdf
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Keywords
Cancer, shared decision making, latent class analysis, risk communication, narratives, personalization, data-driven, SDG 3 - Good Health and Well-being
Citation
Krahmer, E, Clouth, F, Hommes, S, Vromans, R, Pauws, S, Vermunt, J, van de Poll, L & Verbeek, X 2024, Helping Cancer Patients to Choose the Best Treatment : Towards Automated Data-Driven and Personalized Information Presentation of Cancer Treatment Options. in B Haverkort, A de Jongste, P van Kuilenburg & R Vromans (eds), Commit2Data. vol. 124, Open Access Series in Informatics (OASIcs), vol. 124, Schloss Dagstuhl - Leibniz fuer Informatik, pp. 1-20. https://doi.org/10.4230/OASIcs.Commit2Data.3
URI
https://hdl.handle.net/20.500.14602/25858
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