LOGIC REGRESSION FOR DIAGNOSTIC CLASSIFICATION BY MEANS OF BIOMARKER PANELS

Journal Title: Colloquium Biometricum; Colloquium Biometricum (Online) - Year 2016, Vol 46, Issue

Abstract

Biomarkers can indicate a variety of health or disease characteristics, including the level or type of exposure to an environmental factor, genetic susceptibility, genetic responses to exposures, markers of subclinical or clinical disease, or indicators of response to therapy. In this paper we presented using the logic regression for diagnostic classification by means of biomarker panels. The sample collective comprised 389 highly characterized rheumatoid artritis patients and 390 controls, composed of 200 healthy and 190 osteoarthritis samples. The predictive panel consisted of the most promising 11 biomarkers for the early diagnosis of rheumatoid artritis, collected in serum. Obtained results show that the Logic II is the simplest model and performs well, resulting in the lowest misclassification error rate on the test set.

Authors and Affiliations

Jan Bocianowski, Kamila Nowosad

Keywords

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  • EP ID EP190145
  • DOI -
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How To Cite

Jan Bocianowski, Kamila Nowosad (2016). LOGIC REGRESSION FOR DIAGNOSTIC CLASSIFICATION BY MEANS OF BIOMARKER PANELS. Colloquium Biometricum; Colloquium Biometricum (Online), 46(), 1-8. https://europub.co.uk/articles/-A-190145