지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.10 No.4
- 발행연도
- 2021.8
- 수록면
- 323 - 329 (7page)
- DOI
- 10.5573/IEIESPC.2021.10.4.323
이용수
초록· 키워드
오류제보하기
There is no precise treatment available for COVID-19, but treatment of a number of signs/symptoms is possible. This treatment is provided in accordance with the clinical position of the patient. Furthermore, supplementary care is proven as efficient for infected people. COVID-19 prediction techniques follow various steps, which include dataset collection, pre-processing, feature extraction, and classification. Numerous COVID-19 prediction techniques have been proposed in the literature. In this paper, various techniques are systematically reviewed on the basis outcomes, advantages, and disadvantages.
목차
Abstract
1. Introduction
2. Literature Review
3. Conclusion and Future Scope
References
참고문헌 (20)
참고문헌 신청
Yifan Yang, Wenwu Yu, Duxin Chen, “Prediction of COVID-19 spread via LSTM and the deterministic SEIR model”, 2020, 39th Chinese Control Conference (CCC) Article (CrossRefLink)
Suraj Bodapati, Harika Bandarupally, M Trupthi, “COVID-19 Time Series Forecasting of Daily Cases, Deaths Caused and Recovered Cases using Long Short Term Memory Networks”, 2020, IEEE 5th International Conference on Computing Communication and Automation (ICCCA) Article (CrossRefLink)
Hanqing Chao, Xi Fang, Pingkun Yan, “Integrative analysis for COVID-19 patient outcome prediction”, 2020, Medical Image Analysis Article (CrossRefLink)
Danish Rafiq, Suhail Ahmad Suhail, Mohammad Abid Bazaz, “Evaluation and prediction of COVID 19 in India: A case study of worst hit states”, 2020, Chaos, Solitons & Fractals Article (CrossRefLink)
Farah Shahid, AneelaZameer, Muhammad Muneeb, “Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM”, 2020, Chaos, Solitons & Fractals Article (CrossRefLink)
Suraj Bodapati, Harika Bandarupally, M Trupthi, “COVID-19 Time Series Forecasting of Daily Cases, Deaths Caused and Recovered Cases using Long Short Term Memory Networks”, 2020, IEEE 5th International Conference on Computing Communication and Automation (ICCCA) Article (CrossRefLink)
Hanqing Chao, Xi Fang, Pingkun Yan, “Integrative analysis for COVID-19 patient outcome prediction”, 2020, Medical Image Analysis Article (CrossRefLink)
Danish Rafiq, Suhail Ahmad Suhail, Mohammad Abid Bazaz, “Evaluation and prediction of COVID 19 in India: A case study of worst hit states”, 2020, Chaos, Solitons & Fractals Article (CrossRefLink)
Farah Shahid, AneelaZameer, Muhammad Muneeb, “Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM”, 2020, Chaos, Solitons & Fractals Article (CrossRefLink)
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