Lung Cancer Intelligent Prediction System Using CNN

The mortality rate from Lung Cancer is high, and the disease is notoriously difficult to treat. It was the third most frequent mortality reason for women and the leading cause of male mortality, according to data compiled by the International Agency for Research on Cancer (IARC) Cancer Research Facility. Additionally, they provided rates of cancer occurrence and mortality for a total of 36 different cancers occurring in 185 different countries. Typically, early tumor detection is essential for effective therapy. Early cancers can be efficiently examined to help patients recover quickly. Traditional medical imaging techniques, such as X-rays, CT scans, MRIs, etc., offer little promise for lung tumor identification. CNNs are capable of exact image processing. This paper provides a probabilistic deep 2D CNN diagnosis method for lung cancer (CNNs). This algorithm is considered the best in image classification, which gives better results, making the proposed system more efficient. The accuracy values obtained are 86%, the recall of 92%, and the F1-score is 87%.