OPEN ACCESS JSEA Improves Treatment Programs of Lung Cancer Using Data Mining Techniques

Copyright © 2014 Zakaria Suliman Zubi, Rema Asheibani Saad. This is an open access article distributed under the Creative Com-mons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property Zakaria Suliman Zubi, Rema Asheibani Saad. All Copyright © 2014 are guarded by law and by SCIRP as a guardian. Lung cancer is a deadly disease, but there is a big chance for the patient to be cured if he or she is correctly di-agnosed in early stage of his or her case. At a first glance, lung X-ray chest films being considered as the most reliable method in early detection of lung cancers, the serious mistake in some diagnosing cases giving bad re-sults and causing the death, the computer aided diagnosis systems are necessary to support the medical staff to achieve high capability and effectiveness. Clinicians could predict patient’s behavior future and improve treat-ment programs by using data mining techniques and they can be better managing the health of patients today, in addition they do not become the problems of tomorrow. The lung cancer biological database which contains the medical images (chest X-ray) classifies the digital X-ray chest films into three categories: normal, benign and malignant. The normal ones are those characterizing a healthy patient (non nodules);, lung nodules can be eithe