Support vector machine based prediction model for discrimination of malignant pulmonary nodules from benign nodules

Yan Wu, Emmanuel Zachariah, Judith K. Amorosa, Anjani Naidu, Mina L. Labib, Jamil Shaikh, Donna Eckstein, Sinae Kim, John E. Langenfeld, Joseph Aisner, John L. Nosher, Robert S. Dipaola, David J. Foran

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Lung cancer is the leading cause of cancer death in the United States and worldwide. Most patients are diagnosed at an advanced stage, usually stage III or IV. Identification of lung cancer patients at an early stage might enable oncologists to surgically remove the tumors. Currently, low dose CT scans are used to identify the malignant nodules in high risk patients. However, screening CT scans yield a high rate of falsepositive results. A prediction model was developed for improved discrimination of malignant nodules from benign nodules in patients who underwent lung screening CT. CT images and clinical outcomes of 39 patients were obtained from the National Lung Screening Trial (NLST), National Cancer Institute, National Institute of Health. Images were analyzed to extract computational features relevant to malignancy prediction. A Support Vector Machine (SVM) based model was developed to predict the malignancy of nodules. During pilot studies, our model achieved the following prediction performance: Accuracy of 0.74, sensitivity of 0.85, and specificity of 0.61.

Original languageEnglish
Title of host publicationBIOIMAGING 2016 - 3rd International Conference on Bioimaging, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
EditorsJames Gilbert, Ana Fred, Carla Quintao, Jan Sliwa, Haim Azhari, Carolina Ruiz, Hugo Gamboa, Hesham Ali
Pages129-133
Number of pages5
ISBN (Electronic)9789897581700
StatePublished - 2016
Event3rd International Conference on Bioimaging, BIOIMAGING 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016 - Rome, Italy
Duration: Feb 21 2016Feb 23 2016

Publication series

NameBIOIMAGING 2016 - 3rd International Conference on Bioimaging, Proceedings; Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016

Conference

Conference3rd International Conference on Bioimaging, BIOIMAGING 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016
Country/TerritoryItaly
CityRome
Period2/21/162/23/16

Bibliographical note

Publisher Copyright:
© 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

Keywords

  • Benign nodules
  • Malignant nodules
  • Prediction model
  • Pulmonary nodules
  • Support vector machine

ASJC Scopus subject areas

  • Biomedical Engineering
  • Electrical and Electronic Engineering

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