Abstract
Lung Cancer is the leading cause of death among all the cancers’ in today’s world. The survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of the patient records can help in diagnosing cancer during Stage 1. Using a multi-class neural networks helps to identify the disease during its stage 1 itself. The implementation of multi-class neural networks has yielded an accuracy of 100%. The model created using the neural networks approach helps to identify lung cancer during Stage 1 itself, thus the survival rate of the patients can be increased. This model can serve as pre-diagnosis tool for the practitioners.
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Rajan, J.R., Chelvan, A.C. & Duela, J.S. Multi-Class Neural Networks to Predict Lung Cancer. J Med Syst 43, 211 (2019). https://doi.org/10.1007/s10916-019-1355-9
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DOI: https://doi.org/10.1007/s10916-019-1355-9