Abstract
In recent decades, the investigation based on the molecular level for the classification of cancer is becoming trending research topic for several researchers to identify the type of cancer based on the gene expression data. Analyzing large number of gene characteristics offered in-depth classification problem for cancer types. These characteristics help in understanding the gene functions and interaction between the abnormal and normal conditions of it. Under various conditions, the expression data of gene to genes behavior is monitored by this characteristic. In this paper, a deep reinforcement learning (DRL) model is proposed for the effective analysis of gene expression data to find the type of cancer. The dataset of gene expression is used for analyzing the model for predicting the cancer types. Furthermore, the simulation results show that the proposed DRL model can predict the cancer type by obtaining a 97.8% of accuracy when compared with other existing models.
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Prathik, A., Vinodhini, M., Karthik, N., Ebenezer, V. (2022). Prediction of Carcinoma Cancer Type Using Deep Reinforcement Learning Technique from Gene Expression Data. In: Hemanth, D.J., Pelusi, D., Vuppalapati, C. (eds) Intelligent Data Communication Technologies and Internet of Things. Lecture Notes on Data Engineering and Communications Technologies, vol 101. Springer, Singapore. https://doi.org/10.1007/978-981-16-7610-9_40
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DOI: https://doi.org/10.1007/978-981-16-7610-9_40
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