Application of recommender system methods for therapy decision support

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

In this paper two approaches for facilitating therapy decision support are proposed and compared. Both approaches, the Collaborative Recommender and hybrid Demographic-based Recommender, are based on recommender system methods which origin from the field of product recommendation in e-commerce applications. An exemplary dataset comprising health record excerpts of patients suffering from the skin disease psoriasis is used for evaluating both approaches. The approaches estimate the outcome of a subset of systemic therapies to support the medical practitioner in making therapy decisions for a specific patient and time, i.e. consultation under consideration. Both systems proved to work and are capable of assisting medical practitioners prospectively with making appropriate therapy decisions.

Details

Original languageEnglish
Title of host publication2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (electronic)978-1-5090-3370-6
Publication statusPublished - 18 Nov 2016
Peer-reviewedYes

Conference

Title18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016
Duration14 - 17 September 2016
CityMunich
CountryGermany

External IDs

Scopus 85006387039
ORCID /0000-0001-7457-6481/work/162845193

Keywords

Keywords

  • recommender system methods, therapy decision support