PREDICTION OF POST-SURGICAL SURVIVAL OF LUNG CANCER PATIENTS AFTER THORACIC SURGERY USING DATA MINING TECHNIQUES.

Abstract

Lung cancer is one of the common forms of cancer in today's world. Majority of lung cancers can be diagnosed and cured. Consumption of tobacco is the major reason for lung cancer. Lung cancers are categorized as small cell and non-small cell cancers. Thoracic surgery is one of the way to diagnose lung cancer if it is detected at an early stage. Hence it is better to cure lung cancer at the beginning stage. Patients survival cannot be predicted by the surgery alone. Hence if the patient's survival cannot be extended for a year after surgery, then the factors for the death remains a mystery. In order to overcome this problem, we have used data mining techniques in this paper to detect the patient's survival. The main objective of this paper is to correlate and evaluate various data mining algorithms on predicting the survival of lung cancer patients after thoracic surgery. This paper also explains about a new methodology by combining data mining algorithms for the prediction. This paper also explains the factors that are responsible for the death of the patients after thoracic surgery. Copy Right, IJAR, 2017,. All rights reserved.