A Review Article on Prediction of Lung Cancer using Image Processing and Machine Learning Approaches

A wide variety of subtypes of cancer have been discovered. Early cancer research today requires that cancer forms be screened and treated in a timely manner because it aids in the medical treatment of patients. In the fields of biomedicine and bioinformatics, various research has investigated "the use of machine learning and deep learning" to classify cancer patients as having a high or low risk of relapse. Cancer treatment and research have been affected by these methods. It is necessary to employ machine learning techniques when working with enormous datasets in order to determine the most essential properties. "Artificial neural networks (ANN), support vector machines (SVMs), and decision trees can be used to construct cancer cure prediction models (DTs)". This means that while ML techniques can help us better understand how cancer grows, they are not yet ready to be applied in daily clinical practice. "In this study, the ML and DL approaches for cancer progression modeling are explored. Certain ML, input, and data sample supervisions are often used".