ArticleApplied intelligence (Dordrecht, Netherlands)2021
Intelligent system for COVID-19 prognosis: a state-of-the-art survey.
Article in Applied intelligence (Dordrecht, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- COVID-19 health data prediction: a critical evaluation of CNN-based approaches.Scientific reports · 2025Article
- A survey of machine learning-based methods for COVID-19 medical image analysis.Medical & biological engineering & computing · 2023Review
- Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives.Biomedical signal processing and control · 2023Review
- Using fused Contourlet transform and neural features to spot COVID19 infections in CT scan images.Intelligent systems with applications · 2023Article
- A survey on the role of artificial intelligence in managing Long COVID.Frontiers in artificial intelligence · 2023Review
- ISW-LM: An intensive symptom weight learning mechanism for early COVID-19 diagnosis.Computers in biology and medicine · 2022Article
- A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patients.Medical & biological engineering & computing · 2022Review
- Interactive framework for Covid-19 detection and segmentation with feedback facility for dynamically improved accuracy and trust.PloS one · 2022Article
- Comparative Study Based on Analysis of Coronavirus Disease (COVID-19) Detection and Prediction Using Machine Learning Models.SN computer science · 2022Review
- Contribution of Deep-Learning Techniques Toward Fighting COVID-19: A Bibliometric Analysis of Scholarly Production During 2020.IEEE access : practical innovations, open solutions · 2022Article
- Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysis: A case study in the capitals of Brazil.Expert systems with applications · 2021Article
- Impact of COVID-19 on IoT Adoption in Healthcare, Smart Homes, Smart Buildings, Smart Cities, Transportation and Industrial IoT.Sensors (Basel, Switzerland) · 2021Review
- The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic.Information systems frontiers : a journal of research and innovation · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
This 21st century is notable for experiencing so many disturbances at economic, social, cultural, and political levels in the entire world. The outbreak of novel corona virus 2019 (COVID-19) has been treated as a Public Health crisis of global Concern by the World Health Organization (WHO). Various outbreak models for COVID-19 are being utilized by researchers throughout the world to get well-versed decisions and impose significant control measures. Amid the standard methods for COVID-19 worldwide epidemic prediction, easy statistical, as well as epidemiological methods have got more consideration by researchers and authorities. One main difficulty in controlling the spreading of COVID-19 is the inadequacy and lack of medical tests for detecting as well as identifying a solution. To solve this problem, a few statistical-based advances are being enhanced and turn into a partial resolution up-to some level. To deal with the challenges of the medical field, a broad range of intelligent based methods, frameworks, and equipment have been recommended by Machine Learning (ML) and Deep Learning. As ML and DL have the ability of identifying and predicting patterns in complex large datasets, they are recognized as a suitable procedure for producing effective solutions for the diagnosis of COVID-19. In this paper, a perspective research has been conducted in the applicability of intelligent systems such as ML, DL and others in solving COVID-19 related outbreak issues. The main intention behind this study is (i) to understand the importance of intelligent approaches such as ML and DL for COVID-19 pandemic, (ii) discussing the efficiency and impact of these methods in the prognosis of COVID-19, (iii) the growth in the development of type of ML and advanced ML methods for COVID-19 prognosis,(iv) analyzing the impact of data types and the nature of data along with challenges in processing the data for COVID-19,(v) to focus on some future challenges in COVID-19 prognosis to inspire the researchers for innovating and enhancing their knowledge and research on other impacted sectors due to COVID-19.
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Registered trials
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