Lung Cancer Detection using Evolutionary Machine learning and Deep learning: A survey

Lung Cancer is one of the world’s peak-level types of cancer. There are so many people are died due to lung cancer diseases. Early identification of tumors would facilitate in sparing a vast number of lives globally consistently. Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. Recently, for creating medical image classification problems, machine learning (ML) and deep learning (DL) have emerged as two of the most popular and commonly utilized approaches. Furthermore, employing chest CT scans from pneumonia patients, ML and DL models outperformed conventional approaches in effectiveness. The structure and parameters of ML and DL models can be optimized using evolutionary algorithms (EA). This survey aims to overview the recent works in lung cancer detection-based ML and DL models that EA has optimized.