A hybrid model of deep learning features and clinical features for severe cases predication of COVID-19

Titinunt Kitrungrotsakul; Qingqing Chen; Huitao Wu; Preeyanuch Srichola; Hongjie Hu; Wenchao Zhu; Chao Chen; Fangyi Xu; Yong Zhou; Lanfen Lin; Ruofeng Tong; Jingsong Li; Yen-Wei Chen

doi:10.1117/12.2655213

7 April 2023 A hybrid model of deep learning features and clinical features for severe cases predication of COVID-19

Titinunt Kitrungrotsakul, Qingqing Chen, Huitao Wu, Preeyanuch Srichola, Hongjie Hu, Wenchao Zhu, Chao Chen, Fangyi Xu, Yong Zhou, Lanfen Lin, Ruofeng Tong, Jingsong Li, Yen-Wei Chen

Author Affiliations +

Proceedings Volume 12465, Medical Imaging 2023: Computer-Aided Diagnosis; 1246537 (2023) https://doi.org/10.1117/12.2655213
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

COVID-19 has spread around the world since 2019. Approximately 6.5% of COVID-19 a risk of developing severe disease with high mortality rate. To reduce the mortality rate and provide appropriate treatment, this research established an integrated models with to predict the clinical outcome of COVID-19 patients with clinical, deep learning and radiomics features. To obtain the optimal feature combination for prediction, 9 clinical features combination was selected from all available clinical factors after using LASSO, 18 deep learning features from U-Net architecture, and9radiomics features from segmentation result. A total of 213 COVID-19 patients and 335 non-COVID-19 patients from5hospitals were enrolled and used as training and test sample in this research. The proposed model obtained an accuracy, precision, recall, specificity, F1-score and ROC curve of 0.971, 0.943, 0.937, 0.974, 0.941 and 0.979, respectively, which exceeds the related work using only clinical, deep learning or radiomics factors.

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Titinunt Kitrungrotsakul, Qingqing Chen, Huitao Wu, Preeyanuch Srichola, Hongjie Hu, Wenchao Zhu, Chao Chen, Fangyi Xu, Yong Zhou, Lanfen Lin, Ruofeng Tong, Jingsong Li, and Yen-Wei Chen "A hybrid model of deep learning features and clinical features for severe cases predication of COVID-19", Proc. SPIE 12465, Medical Imaging 2023: Computer-Aided Diagnosis, 1246537 (7 April 2023); https://doi.org/10.1117/12.2655213

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