Predicting the risk of squamous dysplasia and esophageal squamous cell carcinoma using minimum classification error method.
Early detection of squamous dysplasia and esophageal squamous cell carcinoma is of great importance. Adopting computer aided algorithms in predicting cancer risk using its risk factors can serve in limiting the clinical screenings to people with higher risks. In the present study, we show that the application of an advanced classification method, the Minimum Classification Error, could considerably enhance the classification performance in comparison to the logistic regression model and the variable structure fuzzy neural network, as the latest successful methods. The results yield the accuracy of 89.65% for esophageal squamous cell carcinoma, and 88.42% for squamous dysplasia risk prediction.
Complex Systems and Cybernetic Control Lab., Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 1591634311, Tehran, Iran.
Motahareh
M
Moghtadaei
Complex Systems and Cybernetic Control Lab., Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 1591634311, Tehran, Iran. Electronic address: mrhashemigolpayegani@aut.ac.ir.
Mohammad Reza
MR
Hashemi Golpayegani
Speech Lab., Faculty of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 1591634311, Tehran, Iran.
Farshad
F
Almasganj
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Digestive Disease Research Center, Shariati Hospital, Tehran University of Medical Sciences, P.O. Box 1411713135, Tehran, Iran.
Arash
A
Etemadi
Womens College Research Institute, Womens College Hospital, University of Toronto, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
Mohammad R
MR
Akbari
Digestive Disease Research Center, Shariati Hospital, Tehran University of Medical Sciences, P.O. Box 1411713135, Tehran, Iran.
Reza
R
Malekzadeh
D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000453:epidemiology*; D055088:Early Detection of Cancer / Q000379:methods*; D004938:Esophageal Neoplasms / Q000453:epidemiology*; D000077277:Esophageal Squamous Cell Carcinoma; D006801:Humans; D016011:Normal Distribution; D011230:Precancerous Conditions / Q000453:epidemiology*; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity
Cancer prediction; Classification; Early detection of cancer; Esophageal squamous cell carcinoma; Risk factors; Squamous dysplasia