Cancer subtype identification using deep learning approach

Arida Ferti Syafiandini, Ito Wasito, Setiadi Yazid, Aries Fitriawan, Mukhlis Amien

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

5 Citations (Scopus)

Abstract

In this paper, a framework using deep learning approach is proposed to identify two subtypes of human colorectal carcinoma cancer. The identification process uses information from gene expression and clinical data which is obtained from data integration process. One of deep learning architecture, multimodal Deep Boltzmann Machines (DBM) is used for data integration process. The joint representation gene expression and clinical is later used as Restricted Boltzmann Machines (RBM) input for cancer subtype identification. Kaplan Meier survival analysis is employed to evaluate the identification result. The curves on survival plot obtained from Kaplan Meier analysis are tested using three statistic tests to ensure that there is a significant difference between those curves. According to Log Rank, Generalized Wilcoxon and Tarone-Ware, the two groups of patients with different cancer subtypes identified using the proposed framework are significantly different.

Original languageEnglish
Title of host publicationProceeding - 2016 International Conference on Computer, Control, Informatics and its Applications
Subtitle of host publicationRecent Progress in Computer, Control, and Informatics for Data Science, IC3INA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages108-112
Number of pages5
ISBN (Electronic)9781509023233
DOIs
Publication statusPublished - 23 Feb 2017
Event2016 International Conference on Computer, Control, Informatics and its Applications, IC3INA 2016 - Tangerang, Indonesia
Duration: 3 Oct 20165 Oct 2016

Publication series

NameProceeding - 2016 International Conference on Computer, Control, Informatics and its Applications: Recent Progress in Computer, Control, and Informatics for Data Science, IC3INA 2016

Conference

Conference2016 International Conference on Computer, Control, Informatics and its Applications, IC3INA 2016
CountryIndonesia
CityTangerang
Period3/10/165/10/16

Keywords

  • cancer subtype
  • deep learning
  • multimodal DBM
  • RBM

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