The application of artificial neural networks and decision tree model in predicting post-operative complication for gastric cancer patients.
OBJECTIVE
Gastric cancer remains a leading cause of death worldwide. Post-operative complication is one important factor which causes mortality of gastric cancer patients after gastrectomy. Better prediction of post-operative complication before gastrectomy can significantly reduce post-operative mortality and morbidity. Therefore, 3 data mining techniques were applied in this study on improving prediction of post-operative complication.


METHODS
A retrospective study was performed on 521 patients from 3 over 2,000 acute-bed medical centers in Taiwan during February 2002 to October 2004. Pre- and post-operative clinical data were collected and analyzed by applying 3 data mining techniques, included Artificial Neural Networks (ANN), Decision Tree (DT) and Logistic Regression (LR).


RESULTS
Results of this study indicated that ANN was a better technique than DT and LR in predicting post-operative complication. Nutritious status, pathological characteristics and operational characteristics were important predictors of post-operative complication.


CONCLUSIONS
Further study on predicting postoperative complication in gastric cancer patients is still important. However, how to combine different data mining techniques to improve accuracies of prediction will be another important issue for clinicians and researchers.
Chien
Ching-Wen
CW
Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei, Taiwan.
Lee
Yi-Chih
YC
Ma
Tsochiang
T
Lee
Tian-Shyug
TS
Lin
Yang-Chu
YC
Wang
Weu
W
Lee
Wei-Jei
WJ
D000368:Aged; D000369:Aged, 80 and over; D003663:Decision Trees; D005260:Female; D005743:Gastrectomy; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D016571:Neural Networks, Computer; D011183:Postoperative Complications / Q000175:diagnosis / Q000209:etiology* / Q000401:mortality; D011379:Prognosis; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D013274:Stomach Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000473:pathology / Q000601:surgery*