A Comprehensive Review on Lung Cancer Prediction Using ML and DL Techniques

Lung Cancer is the leading cause of cancer-related death worldwide. Because it speeds up and improves the process that follows clinical board, early detection, prediction, and diagnosis of lung cancer has therefore become crucial. Lung cancer is a dangerous type of cancer that is hard to find. Because it typically results in demise for both women and men, it is more important for caretakers to promptly and accurately check nodules. As a result, a number of methods have been used to discoverthe lung cancer earlier. This paper presents a review analysis of various Deep Learning (DL) and Machine Learning (ML)based models for the detection of lung cancer. It can now be diagnosed using many different techniques, most of which use CT scan images and some that use x-ray images. In addition, different segmentation algorithms are combined with multiple classifier techniques for the detection of lung cancer nodules through image data. In general the CT scan images are used majorly for the identification of cancerous cells. Additionally, results from DL based strategies were more accurate than those from strategies that were applied using typical ML techniques.