Therapy Decision Support Based on Recommender System Methods

We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to...

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Main Authors: Gräßer, Felix, Beckert, Stefanie, Küster, Denise, Schmitt, Jochen, Abraham, Susanne, Malberg, Hagen, Zaunseder, Sebastian
Other Authors: Hindawi,
Format: Article
Language:English
Published: Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden 2017
Subjects:
Online Access:http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-226869
http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-226869
http://www.qucosa.de/fileadmin/data/qucosa/documents/22686/8659460%20%281%29.pdf
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spelling ndltd-DRESDEN-oai-qucosa.de-bsz-14-qucosa-2268692017-07-22T03:30:59Z Therapy Decision Support Based on Recommender System Methods Gräßer, Felix Beckert, Stefanie Küster, Denise Schmitt, Jochen Abraham, Susanne Malberg, Hagen Zaunseder, Sebastian Datengesteuerte Therapieentscheidungsunterstützung Kollaborative Recommender Demographische Recommender Autoimmunhautkrankheit Psoriasis Technische Universität Dresden Publikationsfonds data-driven therapy decision support Collaborative Recommender Demographic-based Recommender autoimmune skin disease psoriasis Technische Universität Dresden Publishing Fund ddc:610 rvk:XA 10000 We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system. Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden Hindawi, 2017-07-21 doc-type:article application/pdf http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-226869 urn:nbn:de:bsz:14-qucosa-226869 http://www.qucosa.de/fileadmin/data/qucosa/documents/22686/8659460%20%281%29.pdf Journal of Healthcare Engineering (2017) , 2017. ISSN: 2040-2309. DOI: 10.1155/2017/8659460. Artikel-Nr.: 8659460 eng
collection NDLTD
language English
format Article
sources NDLTD
topic Datengesteuerte Therapieentscheidungsunterstützung
Kollaborative Recommender
Demographische Recommender
Autoimmunhautkrankheit
Psoriasis
Technische Universität Dresden
Publikationsfonds
data-driven therapy decision support
Collaborative Recommender
Demographic-based Recommender
autoimmune skin disease
psoriasis
Technische Universität Dresden
Publishing Fund
ddc:610
rvk:XA 10000
spellingShingle Datengesteuerte Therapieentscheidungsunterstützung
Kollaborative Recommender
Demographische Recommender
Autoimmunhautkrankheit
Psoriasis
Technische Universität Dresden
Publikationsfonds
data-driven therapy decision support
Collaborative Recommender
Demographic-based Recommender
autoimmune skin disease
psoriasis
Technische Universität Dresden
Publishing Fund
ddc:610
rvk:XA 10000
Gräßer, Felix
Beckert, Stefanie
Küster, Denise
Schmitt, Jochen
Abraham, Susanne
Malberg, Hagen
Zaunseder, Sebastian
Therapy Decision Support Based on Recommender System Methods
description We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.
author2 Hindawi,
author_facet Hindawi,
Gräßer, Felix
Beckert, Stefanie
Küster, Denise
Schmitt, Jochen
Abraham, Susanne
Malberg, Hagen
Zaunseder, Sebastian
author Gräßer, Felix
Beckert, Stefanie
Küster, Denise
Schmitt, Jochen
Abraham, Susanne
Malberg, Hagen
Zaunseder, Sebastian
author_sort Gräßer, Felix
title Therapy Decision Support Based on Recommender System Methods
title_short Therapy Decision Support Based on Recommender System Methods
title_full Therapy Decision Support Based on Recommender System Methods
title_fullStr Therapy Decision Support Based on Recommender System Methods
title_full_unstemmed Therapy Decision Support Based on Recommender System Methods
title_sort therapy decision support based on recommender system methods
publisher Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden
publishDate 2017
url http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-226869
http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-226869
http://www.qucosa.de/fileadmin/data/qucosa/documents/22686/8659460%20%281%29.pdf
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AT kusterdenise therapydecisionsupportbasedonrecommendersystemmethods
AT schmittjochen therapydecisionsupportbasedonrecommendersystemmethods
AT abrahamsusanne therapydecisionsupportbasedonrecommendersystemmethods
AT malberghagen therapydecisionsupportbasedonrecommendersystemmethods
AT zaunsedersebastian therapydecisionsupportbasedonrecommendersystemmethods
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