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| Artificial Neural Network for Lung Cancer Detection |
Ola Mohammed Abu Kweik, Mohammed Atta Abu Hamid, Samer Osama Sheqlieh, Bassem S. Abu-Nasser, Samy S. Abu-Naser
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Abstract:
The effectiveness of cancer prediction system helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status. The dataset is collected from the data world website. In this paper, we proposed an Artificial Neural Network for detecting whether lung cancer is found or not in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the patient as input variables for the proposed ANN model. The proposed model was trained, and validated using the lung cancer dataset. The proposed model was evaluated and tested. The accuracy rate it gave us was 99.01 %.
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