以類神經網路及分類迴歸樹輔助肝癌病患預測存活情形

Translated title of the contribution: Prediction of survival in patients with liver cancer using artificial neural networks and classification and regression trees

G. Mei Chen, Chien-Yeh Hsu, Hung Wen Chiu, B. A I Chyi-Huey, W. U. Po-Hsun

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Objectives: This study created a survival prediction model for liver cancer using data mining algorithms. Methods: The data were collected from the cancer registry of a medical center in Northern Taiwan between 2004 and 2008. A total of 227 patients were newly diagnosed with liver cancer during this time. Following a literature review, expert consultation, and collection of patients' data, nine variables pertaining to liver cancer survival rates were analyzed using t-tests and chi-square tests. Six variables were significant. An artificial neural network (ANN) and a classification and regression tree (CART) algorithm were adopted as prediction models. The models were tested in three conditions: one variable (clinical stage alone), six significant variables, and all nine variables (significant and non-significant). Five-year survival was the output prediction. Results: The ANN model with nine input variables was a superior predictor of survival (p

Translated title of the contributionPrediction of survival in patients with liver cancer using artificial neural networks and classification and regression trees
Original languageChinese (Traditional)
Pages (from-to)481-493
Number of pages13
JournalTaiwan Journal of Public Health
Volume30
Issue number5
Publication statusPublished - Oct 2011

Keywords

  • Artificial neural networks
  • Classification and regression trees
  • Liver cancer
  • Prediction model

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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