Lung cancer is a deadly disease, but there is a
big chance for the patient to be cured if he or she is correctly diagnosed 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 results
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 treatment 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 either benign
(non-cancerous) or malignant (cancer). Two steps are
major in computer-aided diagnosis systems: pattern
recognition approach, which is a combination of a feature extraction process
and a classification process using neural network classifier.
Cite this paper
Z. Zubi and R. Saad, "Improves Treatment Programs of Lung Cancer Using Data Mining Techniques," Journal of Software Engineering and Applications
, Vol. 7 No. 2, 2014, pp. 69-77. doi: 10.4236/jsea.2014.72008
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