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Scirj Volume IX, Issue IX, September 2021 Edition
ISSN: 2201-2796

Lung Cancer Radar: Augmentation and categories in diagnosis of lung cancer

Ahmed Mohamed Ahmed Hassan, Mohamed Mahmoud Bakr El-Tohfa, Mohamed Ragab Mohamed El-Morsy

Abstract: The crucial issue in dealing with lung cancer globally is the diagnosis process. for a poor citizen, it could take up to days to determine certainly that he has the tumor, and at this point it would be in the late stage. Plus, from every five people, two are misdiagnosed, and to complete the normal diagnosis steps it takes time, effort, and money; however, in the last decade, computer-based applications proved to be a valuable technique to solve this problem. So, it is decided to construct an application by utilizing artificial intelligence (AI), specifically Machine Learning, to solve the issue of diagnosis by focusing on accuracy and time as design requirements, by predicting if the patient has the tumor or not; besides, the application will determine what is its category: adenocarcinoma and large cell carcinoma; moreover, after testing and training the application for 30 trails (epoch) in the end-user version and using the augmentation technique, the accuracy reached to 94.21%, which is about 1.57 times that of human power. Plus, the time to predict the tumor type did not exceed 3 seconds. It is concluded that the application could clearly reduce the time, effort, and money, which are compensated in the diagnosis procedures, and still produces efficient results.

Reference this Paper: Lung Cancer Radar: Augmentation and categories in diagnosis of lung cancer by Ahmed Mohamed Ahmed Hassan, Mohamed Mahmoud Bakr El-Tohfa, Mohamed Ragab Mohamed El-Morsy published at: "Scientific Research Journal (Scirj), Volume IX, Issue IX, September 2021 Edition, Page 17-21 ".

Search Terms: Artificial Intelligence, Machine learning, augmentation, adenocarcinoma, large cell carcinoma

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