Abstract
Early screening of cancer is crucial for patients’ survival time and quality of life. Based on this, this essay suggests a tumor cell detection technique based on a combination of whale optimization technique is proposed and support vector machine. Firstly, tumor cells are categorized using the support vector machine technique; secondly, the support vector machine's parameters have been optimized using the whale optimization technique to continue increasing the model’s accuracy; eventually, a variety of approaches are dreamed up for comparison in order to confirm the success of the suggested approach. The program's findings demonstrate that the previously proposed model's accuracy is around 5% better than that of the conventional support vector machine training regimen, demonstrating the proposed model's cost effectiveness in the field of breast cancer cell proof of identity.
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Luo, Z., Li, Y., Luo, D., Wang, L., Zhu, J. (2023). Application of WOA-SVM Based Algorithm in Tumor Cell Detection Research. In: Zhang, H., et al. International Conference on Neural Computing for Advanced Applications. NCAA 2023. Communications in Computer and Information Science, vol 1869. Springer, Singapore. https://doi.org/10.1007/978-981-99-5844-3_9
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DOI: https://doi.org/10.1007/978-981-99-5844-3_9
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