Author:
Manocha Ankush,Sood Sandeep Kumar,Bhatia Munish
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Reference46 articles.
1. Ahamad, M.M., Aktar, S., Rashed-Al-Mahfuz, M., Uddin, S., Liò, P., Xu, H., Moni, M.A.: A machine learning model to identify early-stage symptoms of SARS-COV-2 infected patients. Expert Syst. Appl. 160, 113661 (2020). https://doi.org/10.1016/j.eswa.2020.113661
2. Vedaei, S.S., Fotovvat, A., Mohebbian, M.R., Rahman, G.M., Wahid, K.A., Babyn, P., Sami, R.: COVID-SAFE: an IoT-based system for automated health monitoring and surveillance in post-pandemic life. IEEE Access 8, 188538 (2020). https://doi.org/10.1109/ACCESS.2020.3030194
3. Hlaing, P.M., Nopparatjamjomras, T.R., Nopparatjamjomras, S.: Digital technology for preventative health care in Myanmar. Digit. Med. 4(3), 117 (2018). https://doi.org/10.4103/digm.digm_25_18
4. Buch, V., Zhong, A., Li, X., Rockenbach, M.A.B.C., Wu, D., Ren, H., Guan, J., Liteplo, A., Dutta, S., Dayan, I., et al.: Development and validation of a deep learning model for prediction of severe outcomes in suspected covid-19infection. (2011). arXiv preprint arXiv:2103.11269
5. Manocha, A., Bhatia, M.: A novel deep fusion strategy for COVID-19 prediction using multimodality approach. Comput. Electr. Eng. 103, 108274 (2022)