Author : Mohamed Ismail Roushdy
CoAuthors : Nada S. El-Askary,Mohammed A.-M. Salem
Source : Ninth IEEE International Conference on Intelligent Computing and Information Systems, ICICIS 2019
Date of Publication : 12/2019
Abstract : Lung nodule is an abnormal growth of tissues in the lung that can be an onset for lung cancer. Fast detection for those nodules and classifying them will ensure better chances for treatments. Random Forest (RF) is a powerful machine learning algorithm and a state-of-the-art technology that proved to give rewarding results in helping radiologies diagnosing lung pathologies. The paper presents a survey on recent researches made for lung nodule detection and classification using RF. Wide range of datasets can be used for lung nodule detection are listed. Different models with the used features and their results are discussed in this review.
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