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.