Journal of Proteomics & Bioinformatics
Open Access

Eric R Siegel

Publications

• Research Article
  Novel Use of Proteomic Profiles in a Convex-Hull Ensemble Classifier to Predict Gynecological Cancer Patients' Susceptibility to Gastrointestinal Mucositis as Side Effect of Radiation Therapy
  Author(s): Ralph L Kodell, Randy S Haun, Eric R Siegel, Chuanlei Zhang, Angela B Trammel, Martin Hauer-Jensen and Alexander F BurnettRalph L Kodell, Randy S Haun, Eric R Siegel, Chuanlei Zhang, Angela B Trammel, Martin Hauer-Jensen and Alexander F Burnett
  
  Background: Whole-pelvis radiation therapy is common practice in the post-surgical treatment of cervical and endometrial cancer. Gastrointestinal mucositis is an adverse side effect of radiation therapy, and is a primary concern in patient management. We investigate whether proteomic information obtained from blood samples drawn from patients scheduled to receive radiation therapy for gynecological cancers could be used to predict which patients are most susceptible to radiation-induced gastrointestinal mucositis, in order to improve the individualization of radiation therapy. Methods: We use 132 proteins measured on 17 gynecological cancer patients in a convex-hull-based, selectivevoting ensemble classifier to classify each patient into one of two classes: patients who would not (class 1) or would (class 2) develop gastrointestinal mucositis. We employ 20 repetitions of 10-fold cross.. View More»
  DOI: 10.4172/jpb.1000363

  Abstract PDF

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