DETECTION AND DIAGNOSIS OF LUNG CANCER USING CNN BASED ARTIFICIAL INTELLIGENCE

Abstract

Detection and diagnosis at the appropriate time and proper treatment subsequently are quite critical for the well-being of the patient. Any delay during initial referral, evaluation to a definitive diagnosis, treatment, follow-up, and care of the survivor may result in patient outcomes in a negative manner. Both doctors and patients can attribute to delay in diagnosis of lung cancer, as there can be a delay in the commencement of investigations, or there can also be failures at the hospital end in mobilizing records, which can, in turn, lead to delay in treatment. Moreover, patient’s records have been the prime source of information, and the delay by the patient in visiting the doctor at the advent of symptoms can be the main reason for the delay. It has been stressed the importance of continued effort in reducing the delays in diagnosing and treating patients with lung cancer. Screening aims at increasing life expectancy and refining the quality of life, but unfortunately, decades of screening of lung cancer have no survival benefits. In this paper we must find and Detection and diagnosis of lung cancer using CNN BASED Artificial Intelligence. In this method we use different type of techniques.