Artificial neural networks approach to early lung cancer detection
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Lung cancer is rated with the highest incidence and mortality every year compared with other forms of cancer, therefore early detection and diagnosis is essential. Artificial Neural Networks (ANNs) are “artificial intelligence” software which have been used to assess a few prognostic situations. In this study, a database containing 193 patients from Diagnostic and Monitoring of Tuberculosis and Illness of Lungs Ward in Kuyavia and Pomerania Centre of the Pulmonology (Bydgoszcz, Poland) was analysed using ANNs. Each patient was described using 48 factors (i.e. age, sex, data of patient history, results from medical examinations etc.) and, as an output value, the expected presence of lung cancer was established. All 48 features were retrospectively collected and the database was divided into a training set (n=97), testing set (n=48) and a validating set (n=48). The best prediction score of the ANN model (MLP 48-9-2) was above 0.99 of the area under a receiver operator characteristic (ROC) curve. The ANNs were able to correctly classify 47 out of 48 test cases. These data suggest that Artificial Neural Networks can be used in prognosis of lung cancer and could help the physician in diagnosis of patients with the suspicion of lung cancer.
KeywordsArtificial Neural Networks Cancer diagnosis Lung cancer Risk factors
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- Bishop C.M., Neural networks for pattern recognition, New York, NY: Oxford University Press 1995.Google Scholar
- Buciński A., Bączek T., Kaliszan R., Nasal A., Krysiński J., Załuski J., Artificial Neural Network Analysis of Patient and Treatment Variables as a Prognostic Tool in Breast Cancer after Mastectomy, Adv. Clin. Exp. Med., 2005, 14, 973–979Google Scholar
- Luenberger D.G., Ye Y., Linear and nonlinear programming, International Series in Operations Research & Management Science 116 (Third ed.), New York, Springer, 2008, pp. xiv+546Google Scholar
- Chen T.M., Kuschner W.G., Non-tobacco related lung carcinogens. Lung cancer principle and practice, In: Harvey P. et al, editors. 3rd ed, Lippincot Williams and Wilkins: 2005. p. 61–73Google Scholar