Abstract
Metastasis and acrometastasis diseases were presented as the tumor in the tongue and hands of the human body. These two diseases may cause cancer to the lungs part of the human body. Metastases have the base in parts of the lung, breast or kidney. In this paper, the lung cancer symptoms can be diagnosed based on the metastases to the tongue images and acrometastases to the hands’ images. The proposed effort composed of feature extraction of tongue and hand images as input by using the Wiener filter processes. A support vector machine in supervised learning models with learning steps can explore the data which can be used for classification and regression scrutiny. The classifier techniques sustain to classify the metastases and acrometastases data. Finally, the classification and regression process can increase accuracy to predict the metastasis and acrometastasis diseases for lungs cancer. The proposed work is implemented using the MATLAB software and classifier increases an accuracy of feature extraction.
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Vidhyalakshmi, A., Priya, C. (2020). Feature Extraction of Metastasis and Acrometastasis Diseases Using the SVM Classifier. In: Peng, SL., Son, L.H., Suseendran, G., Balaganesh, D. (eds) Intelligent Computing and Innovation on Data Science. Lecture Notes in Networks and Systems, vol 118. Springer, Singapore. https://doi.org/10.1007/978-981-15-3284-9_17
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DOI: https://doi.org/10.1007/978-981-15-3284-9_17
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