A Correlation Blockchain Matrix Factorization to Enhance the Disease Prediction Accuracy and Security in IoT Medical Data
Author:
Renuka P.,Booba B.
Publisher
Springer Singapore
Reference31 articles.
1. Wang, H., Huang, Z., Zhang, D., Arief, J., Lyu, T., Tian, J.: Integrating co-clustering and interpretable machine learning for the prediction of intravenous immunoglobulin resistance in kawasaki disease. IEEE Access 8, 97064–97071 (2020) 2. Mohan, S., Thirumalai, C., Srivastava, G.: Effective heart disease prediction using hybrid machine learning techniques. IEEE Access, 1–1 (2019) 3. Castro, L.F.B., Santacruz, L.F.E., Sánchez, M.B.S.: Work of breathing estimation during spontaneous breathing test using machine learning techniques. In: 2020 IEEE Colombian Conference on Applications of Computational Intelligence (IEEE ColCACI 2020), Cali, Colombia, pp. 1–6 (2020). https://doi.org/10.1109/ColCACI50549.2020.9247855 4. Li, J.P., Haq, A.U., Din, S.U., Khan, J., Khan, A., Saboor, A.: Heart disease identification method using machine learning classification in E-healthcare. IEEE Access 8, 107562–107582 (2020) 5. Chen, M., Hao, Y., Hwang, K., Wang, L., Wang, L.: Disease prediction by machine learning over big data from healthcare communities. IEEE Access 5, 8869–8879 (2017)
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