MCLSG:Multi-modal classification of lung disease and severity grading framework using consolidated feature engineering mechanisms

Abobaker Mohammed Qasem Farhan, Shangming Yang, Abdulrahman Q. S. Al-Malahi, Mugahed A. Al-antari

Abstract: Highlights•A novel MCLSG framework is proposed for diagnosing multiple lung disease with severity grading.•Multi-modal deep features are extracted using an adopted CNN model.•Consolidated feature learning model is proposed for accurate prediction of disease severity.•The proposed MCLSG framework achieves accuracy disease detection of 99.64% and severity grading of 88.75%.