In this paper, we present a brief but critic survey of deep learning approaches in solving the remarkable task of lung cancer detection using computerized tomography scans. This is a survey paper that is intended to give the reader the cuttingedge algorithms to solve this task. We reviewed over 20 papers related to this topic to cover the best methods to approach this problem. In addition, our work develops a review not only in the algorithm, but also in the input dataset, the computerized tomography scans. At the end, we conclude with a summary of the current state-of-the-art methods, an overall analysis of the algorithms revised and some considerations to solve the lung cancer classification task in computerized tomography.