COVID-19 Disease Diagnosis using Smart Deep Learning Techniques

M. Kavitha¹ , T. Jayasankar² , P. Maheswara Venkatesh³ , G. Mani³ , C. Bharatiraja This email address is being protected from spambots. You need JavaScript enabled to view it.⁴, and Bhekisipho Twala⁵

¹Department of Electronics and Communication Engineering, K.Ramakrishnan College of Technology, Tiruchirappalli, Tamilnadu, India.
²Department of Electronics and Communication Engineering, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, Tamilnadu, India.
³Department of Computer Science Engineering, University College of Engineering, Arani, Tamilnadu, India.
⁴Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur, 603203, Kanchipuram, Chennai, TN, India.
⁵Faculty of Engineering the Built Environment, Durban University of Technology (DUT), South Africa.

REFERENCES

1. [1] Cheryl A. Glass, Jill C. Cash, and Jenny Mullen. Coronavirus Disease (COVID-19). In Family Practice Guidelines. 2020.
2. [2] World Health Organization (WHO). Modes of transmission of virus causing COVID-19: implications for IPC precaution recommendations. Geneva: World Health Organization;, Available, 2020.
3. [3] Cheryl A. Glass, Jill C. Cash, and Jenny Mullen. Coronavirus Disease (COVID-19). In Family Practice Guidelines. 2020.
4. [4] Dilbag Singh, Vijay Kumar, Vaishali, and Manjit Kaur. Classification of COVID-19 patients from chest CT images using multi-objective differential evolution–based convolutional neural networks. European Journal of Clinical Microbiology and Infectious Diseases, 39(7):1379–1389, 2020.
5. [5] X Mei, HC Lee, K Diao, M Huang, B Lin, C Liu, Z Xie Nature Medicine, and Undefined 2020. Artificial intelligence–enabled rapid diagnosis of patients with COVID-19. Nature Medicine, 2020.
6. [6] Ying Hui Jin, Lin Cai, Zhen Shun Cheng, Hong Cheng, Tong Deng, Yi Pin Fan, Cheng Fang, Di Huang, Lu Qi Huang, Qiao Huang, Yong Han, Bo Hu, Fen Hu, Bing Hui Li, Yi Rong Li, Ke Liang, Li Kai Lin, Li Sha Luo, Jing Ma, Lin Lu Ma, Zhi Yong Peng, Yun Bao Pan, Zhen Yu Pan, Xue Qun Ren, Hui Min Sun, Ying Wang, Yun Yun Wang, Hong Weng, Chao Jie Wei, Dong Fang Wu, Jian Xia, Yong Xiong, Hai Bo Xu, Xiao Mei Yao, Yu Feng Yuan, Tai Sheng Ye, Xiao Chun Zhang, Ying Wen Zhang, Yin Gao Zhang, Hua Min Zhang, Yan Zhao, Ming Juan Zhao, Hao Zi, Xian Tao Zeng, Yong Yan Wang, and Xing Huan Wang. A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version), feb 2020.
7. [7] Samir S. Yadav and Shivajirao M. Jadhav. Deep convolutional neural network based medical image classification for disease diagnosis. Journal of Big Data, 6(1), dec 2019.
8. [8] Shahadat Uddin, Arif Khan, Md Ekramul Hossain, and Mohammad Ali Moni. Comparing different supervised machine learning algorithms for disease prediction. BMC Medical Informatics and Decision Making, 19(1), dec 2019.
9. [9] Ahmad Alimadadi, Sachin Aryal, Ishan Manandhar, Patricia B. Munroe, Bina Joe, and Xi Cheng. Artificial intelligence and machine learning to fight covid-19, apr 2020.
10. [10] Tulin Ozturk, Muhammed Talo, Eylul Azra Yildirim, Ulas Baran Baloglu, Ozal Yildirim, and U. Rajendra Acharya. Automated detection of COVID-19 cases using deep neural networks with X-ray images. Computers in Biology and Medicine, 121, 2020.
11. [11] F Ucar, D Korkmaz Medical Hypotheses, and Undefined 2020. COVIDiagnosis-Net: Deep BayesSqueezeNet based Diagnostic of the Coronavirus Disease 2019 (COVID-19) from X-Ray Images. Medical Hypotheses, 2020.
12. [12] Gurjit S. Randhawa, Maximillian P.M. Soltysiak, Hadi El Roz, Camila P.E. de Souza, Kathleen A. Hill, and Lila Kari. Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study. PLoS ONE, 15(4), apr 2020.
13. [13] Liona C. Poon, Huixia Yang, Anil Kapur, Nir Melamed, Blami Dao, Hema Divakar, H. David McIntyre, Anne B. Kihara, Diogo Ayres-de Campos, Enrico M. Ferrazzi, Gian Carlo Di Renzo, and Moshe Hod. Global interim guidance on coronavirus disease 2019 (COVID-19) during pregnancy and puerperium from FIGO and allied partners: Information for healthcare professionals. International Journal of Gynecology and Obstetrics, 149(3):273–286, jun 2020.
14. [14] Ahmed Abdullah Farid, Gamal Ibrahim Selim, and Hatem Awad A. Khater. A Novel Approach of CT Images Feature Analysis and Prediction to Screen for Corona Virus Disease (COVID-19). International Journal of Scientific & Engineering Research, 11(03):1141–1149, 2020.
15. [15] Yan Li and Liming Xia. Coronavirus disease 2019 (COVID-19): Role of chest CT in diagnosis and management. American Journal of Roentgenology, 214(6):1280– 1286, jun 2020.
16. [16] Buddhisha Udugama, Pranav Kadhiresan, Hannah N. Kozlowski, Ayden Malekjahani, Matthew Osborne, Vanessa Y.C. Li, Hongmin Chen, Samira Mubareka, Jonathan B. Gubbay, and Warren C.W. Chan. Diagnosing COVID-19: The Disease and Tools for Detection, apr 2020.
17. [17] Asmaa Abbas, Mohammed M. Abdelsamea, and Mohamed Medhat Gaber. Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. Applied Intelligence, 2020.
18. [18] Shuai Wang, Bo Kang, Jinlu Ma, Xianjun Zeng, Mingming Xiao, Jia Guo, Mengjiao Cai, Jingyi Yang, Yaodong Li, Xiangfei Meng, and Bo Xu. A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19), 2020.
19. [19] Ali Imran, Iryna Posokhova, Haneya N. Qureshi, Usama Masood, Muhammad Sajid Riaz, Kamran Ali, Charles N. John, MD Iftikhar Hussain, and Muhammad Nabeel. AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app. Informatics in Medicine Unlocked, 20, jan 2020.
20. [20] Xiaowei Xu, Xiangao Jiang, Chunlian Ma, Peng Du, Xukun Li, Shuangzhi Lv, Liang Yu, Yanfei Chen, Junwei Su, Guanjing Lang, Yongtao Li, Hong Zhao, Kaijin Xu, Lingxiang Ruan, and Wei Wu. Deep learning system to screen coronavirus disease 2019 pneumonia, 2020.
21. [21] Mesut To ˘gaçar, Burhan Ergen, and Zafer Cömert. COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest Xray images using fuzzy color and stacking approaches. Computers in Biology and Medicine, 121, 2020.
22. [22] Ali Abbasian Ardakani, Alireza Rajabzadeh Kanafi, U. Rajendra Acharya, Nazanin Khadem, and Afshin Mohammadi. Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks. Computers in Biology and Medicine, 121, 2020.
23. [23] Erik Cuevas. An agent-based model to evaluate the COVID-19 transmission risks in facilities. Computers in Biology and Medicine, 121, 2020.
24. [24] Azath Mubarakali, M. Ashwin, Dinesh Mavaluru, and A. Dinesh Kumar. Design an attribute based health record protection algorithm for healthcare services in cloud environment. Multimedia Tools and Applications, 79(5-6):3943–3956, feb 2020.
25. [25] Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q Duong, and Marzyeh Ghassemi. COVID19 Image Data Collection: Prospective predictions are the future, jun 2020.
26. [26] Halgurd S Maghdid, Aras T Asaad, Kayhan Zrar Ghafoor, Ali Safaa Sadiq, and Muhammad Khurram Khan. Diagnosing COVID-19 Pneumonia from X-Ray and CT Images using Deep Learning and Transfer Learning Algorithms, 2020.
27. [27] Srinath Balasubramanian, Bharatiraja Chokkalingam, Ramesh Krishnamoorthy, and Yusuff Adedayo. Power optimization through FuzzyMinProduct algorithm for voltage assignment in SOC design. Journal of Applied Science and Engineering, 23(4):655–659, 2020.
28. [28] M S Kamalesh, Bharatiraja Chokkalingam, Jeevanantham Arumugam, Sengottaiyan Gomathy, Shanmugavadivel Subramani, and Mansoor Ahmad Shah. An Intelligent Real Time Pothole Detection and Warning System for Automobile Applications Based on IoT Technology. Journal of Applied Science and Engineering, 24(1):77–81, 2021.