Streamlining Cancer Diagnosis and Prognosis System using Hybrid CNN-NPR: Deep Learning Approaches
Keywords:
CNN, Deep Learning, CNN-NPR, Cancer diagnosis, Prognosis systemAbstract
In the context of medical science, advancements in technical infrastructure related to computer and life sciences have enabled the utilization of computational methods for medical diagnosis. As the number of cancer cases continues to rise rapidly, the existing diagnostic system is becoming out dated, necessitating the development of modern, productive, and optimized strategies. Accurately predicting the type of cancer is crucial for the diagnosis and treatment of the disease. Knowledge of cancer genes can significantly assist in comprehending, diagnosing, and identifying the different types of cancer. In this study paper, the identification and prediction of cancer type are achieved through the utilization of hybrid CNN-NPR several researchers have proposed different Convolutional Neural Network (CNN) models to date. Every model focused on a specific group of parameters that were utilized to imitate the gene pattern.
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