TY  - JOUR
T1  - Prediction of Post-Surgical Survival of Lung Cancer Patients after Thoracic Surgery using
Data Mining Techniques
AU - Roshan, S. AU - Rohini, V. 
JO  - International Journal of Soft Computing
VL  - 16
IS  - 3
SP  - 34
EP  - 38
PY  - 2021
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2021.34.38
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2021.34.38
KW  - Lung cancer
KW  -thoracic
KW  -data mining
KW  -prediction
KW  -thoracic surgery
AB  - 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 study 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.
ER  -