A Journeying on Machine Learning and Deep Learning Strategies for Lung Carcinoma Forecasting

Lung cancer, which ranks second globally in terms of prevalence, is a significant factor linked to a lower likelihood of survival. In the context of cancer-related illnesses, it significantly affects survival disparities between sexes. Preventive lung cancer diagnosis is one of the most important ways to improve the prognosis for those who have the disease. A variety of machine learning and deep learning techniques have significantly improved outcomes for lung cancer. To enable early detection of lung cancer, researchers have developed precise prediction models based on machine learning and deep learning techniques. By placing greater emphasis on the dataset augmentation component, that is, expanding the sample size and incorporating ensemble approaches that could aid in defining the various stages of cancer progression, the current research endeavor can be further improved. The article provides a thorough overview of the numerous studies conducted by various researchers that use various technical techniques to explain how lung cancer develops as a predictive strategy.