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  5. Prediction of NB-UVB phototherapy treatment response of psoriasis patients using data mining
 
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Prediction of NB-UVB phototherapy treatment response of psoriasis patients using data mining

Author(s)
Mohamed, Sharifa  
Huang, Bingquan  
Kechadi, Tahar  
Uri
http://hdl.handle.net/10197/9112
Date Issued
2017-12-16
Date Available
2017-12-14T15:34:15Z
Abstract
NB-UVB Phototherapy is one of the most commontreatments administrated by dermatologists for psoriasis patients.Although in general, the treatment results in improving thecondition, it also can worsen it. If a model can predict thetreatment response before hand, the dermatologists can adjustthe treatment accordingly. In this paper, we use data miningtechniques and conduct four experiments. The best performanceof all four experiments was obtained by the stacked classifiermade of hyper parameter tuned Random Forest, kSVM and ANNbase learners, learned using L1-Regularized Logistic Regressionsuper learner.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2017 IEEE
Subjects

Machine learning

Statistics

Web versions
https://muii.missouri.edu/bibm2017/
Language
English
Status of Item
Peer reviewed
Journal
Hu, X. et al. Proceedings: 2017 IEEE International Conference on Bioinformatics and Biomedicine: Nov 13-16, 2017, Kansa City, MO, USA
Conference Details
IEEE International Conference on Bioinformatics and Biomedicine, (BIBM-BHI 2017), Kansas, MO, USA, November 13-16, 2017
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

Size

215.13 KB

Format

Adobe PDF

Checksum (MD5)

529234b272a529c02028575a69543874

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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