Predicting survival of individual patients with esophageal cancer by adaptive neuro-fuzzy inference system approach

Chang Yu Wang, Jinn Tsong Tsai, Chun Hsiung Fang, Tsair Fwu Lee, Jyh Horng Chou*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

17 Scopus citations

Abstract

Abstract Since esophageal cancer has no symptoms in the early stage, it is usually not detected until advanced stages in which treatment is challenging. Integrated treatment provided by a multidisciplinary team is crucial for maximizing the prognosis and survival of patients with esophageal cancer. Currently, clinicians must rely on the cancer staging system for diagnosis and treatment. An accurate and easily applied system for predicting the prognosis of esophageal cancer would be useful for comparing different treatment strategies and for calculating cancer survival probability. This study presents a hazard modeling and survival prediction system based on adaptive neuro-fuzzy inference system (ANFIS) to assist clinicians in prognostic assessment of patients with esophageal cancer and in predicting the survival of individual patients. Expert knowledge was used to construct the fuzzy rule based prognosis inference system for esophageal cancer. Fuzzy logic was used to process the values of input variables rather than categorizing values as normal or abnormal based on cutoffs. After transformation and expansion, censored survival data could be used by the ANFIS for training to establish the risk model for accurately predicting individual survival for different time intervals or for different treatment modalities. Actual values for serum C-reactive protein, albumin, and time intervals were input into the model for use in predicting the survival of individual patients for different time intervals. The curves obtained by the ANFIS approach were fitted to those obtained using the actual values. The comparison results show that the ANFIS is a practical, effective, and accurate method of predicting the survival of esophageal cancer patients.

Original languageEnglish
Article number3039
Pages (from-to)583-590
Number of pages8
JournalApplied Soft Computing Journal
Volume35
DOIs
StatePublished - 21 07 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Elsevier B.V.

Keywords

  • Adaptive fuzzy inference system (ANFIS)
  • Esophageal cancer
  • Radiotherapy
  • Survival analysis

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