Cancer Cell Identification Using CNN Algorithm

  • B. venkatasrilekha chowdary, Dr. R. Beaulah jeyavathana

Abstract

The determination of blood-related maladies includes the recognizable proof and portrayal of a patient's blood test. All things considered, mechanized techniques for recognizing and characterizing the sorts of platelets have significant restorative applications right now. Profound learning may take care of this issue viably. In the proposed framework, convolutional neural system (CNN) is utilized for learning and recognition. A large portion of existing exploration proposed were distinguishes platelet class, while, this work focused on platelet type order and infection ID as a consolidated model. This is accomplished via preparing platelet types as four classes independently and malady discovery preparing (twofold class of ordinary/disease) utilizing CNN calculation. Test results shows that CNN accomplishes more exactness on preparing and approval set.

Published
2020-06-01
How to Cite
B. venkatasrilekha chowdary, Dr. R. Beaulah jeyavathana. (2020). Cancer Cell Identification Using CNN Algorithm. International Journal of Advanced Science and Technology, 29(7s), 4672 - 4678. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/25711