Prediction of lymph node metastasis in gastric cancer patients with neural networks

Artificial neural networks are a kind of pattern classifiers, with growing acceptance in medical and biological research. We applied a single layer perceptron to data of 4302 patients from National Cancer Centre in Tokyo and compared the results to the Maruyama diagnostic system (MDS) and classic st...

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Bibliographic Details
Published in:Cancer letters 1996-12, Vol.109 (1), p.141-148
Main Authors: Droste, Karin, Bollschweiler, Elfriede, Waschulzik, Thomas, Schütz, Thorsten, Engelbrecht, Rolf, Maruyama, Keiichi, Siewert, J.Rüdiger
Format: Article
Language:English
Subjects:
Adult
Aged
Aged, 80 and over
Artificial neural networks
Biological and medical sciences
Computerized diagnosis
Computerized, statistical medical data processing and models in biomedicine
Feedforward neural network
Female
Gastric cancer
Humans
Logistic Models
Lymph node metastasis
Lymphatic Metastasis
Male
Medical management aid. Diagnosis aid
Medical sciences
Middle Aged
Neural Networks (Computer)
Sensitivity and Specificity
Stomach Neoplasms - pathology
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Summary:Artificial neural networks are a kind of pattern classifiers, with growing acceptance in medical and biological research. We applied a single layer perceptron to data of 4302 patients from National Cancer Centre in Tokyo and compared the results to the Maruyama diagnostic system (MDS) and classic statistical analysis with logistic regression. While logistic regression reached no sensitivity and a specificity of 1.00 in median, MDS had a sensitivity of 0.74 and a specificity of 0.75 in median. The perceptron reached a median sensitivity of 0.83 and a median specificity of 0.71.
ISSN:0304-3835
1872-7980
DOI:10.1016/S0304-3835(96)04438-2