Now showing 1 - 2 of 2
  • Publication
    Use of Data Mining Techniques to Predict Short Term Adverse Events Occurrence in NB-UVB Phototherapy Treatments
    (International Journal of Machine Learning and Computing, 2018-04) ; ;
    The prediction of short term adverse events occurrence in phototherapy treatment is important for the dermatologists who administrate phototherapy to adjust the treatment and standardize the clinical outcomes. Recently, a modeling technique which can detect the potential short term adverse events occurrence in phototherapy treatments is required for clinicians. Based on data mining, this study tends to explore the significant features and the class distribution of training data for the short term adverse events occurrence prediction in NB-UVB phototherapy treatments. The experimental results highlight that acceptable prediction accuracy can be achieved by using the significant features and the performance of the classifiers can be significantly improved by sampling 40% of negative class samples in training data, hyper parameter tuning of classifiers and use of stacked classifiers in creating prediction models.
    Scopus© Citations 2  330
  • Publication
    Prediction of NB-UVB phototherapy treatment response of psoriasis patients using data mining
    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.
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