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In healthcare applications, deep learning is a highly valuable tool. It extracts features from raw data to save time and effort for health practitioners. A deep learning model is capable of learning and extracting the features from raw data by itself without any external intervention. On the other hand, shallow learning feature extraction techniques depend on user experience in selecting a powerful feature extraction algorithm. In this article, we proposed a multistage model that is based ondoi:10.1155/2021/6624764 pmid:33575018 pmcid:PMC7861952 fatcat:77re7g5sdrcenj5n73vww6xmdy