Survey On Design and Develop Deep Learning Based Algorithm for Diagnosis and Treatment of Covid -19 Patients

Authors

  • Sonali Tanaji Wategaonkar  Department of Computer Engineering, Zeal College of Engineering and Research, Pune, Maharashtra, India
  • Rashmi Ashtagi  Department of Computer Engineering, Zeal College of Engineering and Research, Pune, Maharashtra, India

Keywords:

Machine Learning, CNN, Covid-19, Django Framework

Abstract

Individuals' strength is severely harmed by the worldwide plague caused by COVID-19. Since its declaration as a global pandemic, the illness has caused damage in a large number of countries in diverse countries throughout the world. A large amount of work has recently been completed by experts, researchers, and a variety of others working at the forefronts to counter the effects of the expanding sickness. In the fight against COVID-19, the combination of man-made brainpower, specifically deep and AI applications, has made a significant contribution by providing an advanced imaginative technique to deal with recognizing, diagnosing, treating, and preventing the infection. We focus primarily on the role of discourse in our suggested project.

References

  1. Nandhini Subramanian , Omar Elharrouss, Somaya Al-Maadeed, Muhammed Chowdhury. “ A review of deep learning-based detection methods for COVID-19” Computers in Biology and Medicine 143 (2022) 105233
  2. Nassif, A.B.; Shahin, I.; Bader, M.; Hassan, A.;Werghi, N. COVID-19 Detection Systems Using Deep-Learning Algorithms Based on Speech and Image Data. Mathematics 2022, 10, 564. https://doi.org/10.3390/math10040564
  3. Ashit Kumar Dutta, 1 Nasser Ali Aljarallah, T. Abirami,4 M. Sundarrajan,5Seifedine Kadry,6 Yunyoung Nam ,7 and Chang-Won Jeong8.” Optimal Deep-Learning-Enabled Intelligent Decision Support System for SARS-CoV-2 Classification”Journal of Healthcare Engineering Volume 2022, Article ID 4130674, 14 pages
  4. Md Rafiul Hassan1 • Walaa N Ismail2 • Ahmad Chowdhury3 • Sharara Hossain4 • Shamsul Huda5 • Mohammad Mehedi Hassan6. “A framework of genetic algorithm‑based CNN on multi‑access edge computing for automated detection of COVID‑19” Accepted: 17 November 2021
  6. Yonghang Tai, Bixuan Gao, Qiong Li, Zhengtao Yu, Chunsheng Zhu, Victor Chang.” Trustworthy and Intelligent COVID-19 Diagnostic IoMT through XR and Deep Learning-based Clinic Data Access”Authorized licensed use limited to: IEEE Xplore. Downloaded on May 14,2021
  7. Suda sheikh.”analysis and predication of covid-19 using regression Models and time series forecasting”IEEE2021.
  8. Sanjay Kumar, Sumant Kumar, Sumant Kumar.” COVID-19 Data Analysis and Prediction Using (Machine Learning) andVaccination update of India”IEEE 2020.
  9. The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team.” The Epidemiological Characteristics of an Outbreak of 2019 NovelCoronavirus Diseases (COVID-19) — China, 2020”IEEE 2020.
  10. Minghuan Wang*, Chen Xia*, Lu Huang*, Shabei Xu*, Chuan Qin*, Jun Liu*, Ying Cao, Pengxin Yu, Tingting Zhu, Hui Zhu, Chaonan Wu, Rongguo Zhang, Xiangyu Chen, Jianming Wang, Guang Du, Chen Zhang, Shaokang Wang, Kuan Chen, Zheng Liu, Liming Xia, Wei Wang.” Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation”Vol 2 October 2020
  11. Ashish U Mandayam, Rakshith.A.C.” Prediction of Covid-19 pandemic based on Regression” 2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)
  12. Pan Zhai a , Yanbing Ding a , Xia Wu b , Junke Long c , Yanjun Zhong d , Yiming Li.” The epidemiology, diagnosis and treatment of COVID-19”2020 Elsevier B.V. and International Society of Chemotherapy. All rights reserved
  13. Yuzhen Zhang1, #, Bin Jiang1,#, Jiamin Yuan1, Yanyun Tao. “The impact of social distancing and epicenter lockdown on the COVID-19 epidemic in mainland China: A data-driven SEIQR model study”2019.
  14. Feng Pan, MD*1,2, Tianhe Ye, MD*1,2, Peng Sun, MD3, Shan Gui1,2, Bo Liang, MD1,2, Lingli Li, MD1,2, Dandan Zheng, PhD4, Jiazheng Wang, PhD4, Richard L. Hesketh, MD, PhD5, Lian Yang, MD1,2, Chua sheng Zheng, MD, PhD1,2.” Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia”IEEE 2019
  15. A. S. Ladkat, S. S. Patankar and J. V. Kulkarni, "Modified matched filter kernel for classification of hard exudate," 2016 International Conference on Inventive Computation Technologies (ICICT), 2016, pp. 1-6, doi: 10.1109/INVENTIVE.2016.7830123
  16. A. S. Ladkat, A. A. Date and S. S. Inamdar, "Development and comparison of serial and parallel image processing algorithms," 2016 International Conference on Inventive Computation Technologies (ICICT), 2016, pp. 1-4, doi: 10.1109/INVENTIVE.2016.7824894.

International Journal of Scientific Research in Science and Technology

Downloads

Published

2022-05-30

Issue

Volume 9, Issue 3, May-June-2022

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sonali Tanaji Wategaonkar, Rashmi Ashtagi "Survey On Design and Develop Deep Learning Based Algorithm for Diagnosis and Treatment of Covid -19 Patients" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 3, pp.594-601, May-June-2022.