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  1. Article: Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review.

    Lalmuanawma, Samuel / Hussain, Jamal / Chhakchhuak, Lalrinfela

    Chaos, solitons, and fractals

    2020  Volume 139, Page(s) 110059

    Abstract: ... pandemic. The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application ... in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and ... in the current situation while tackling the Covid-19 pandemic and ahead.: Conclusion: The ongoing development ...

    Abstract Background and objective: During the recent global urgency, scientists, clinicians, and healthcare experts around the globe keep on searching for a new technology to support in tackling the Covid-19 pandemic. The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application on the previous epidemic encourage researchers by giving a new angle to fight against the novel Coronavirus outbreak. This paper aims to comprehensively review the role of AI and ML as one significant method in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and its related epidemic.
    Method: A selective assessment of information on the research article was executed on the databases related to the application of ML and AI technology on Covid-19. Rapid and critical analysis of the three crucial parameters, i.e., abstract, methodology, and the conclusion was done to relate to the model's possibilities for tackling the SARS-CoV-2 epidemic.
    Result: This paper addresses on recent studies that apply ML and AI technology towards augmenting the researchers on multiple angles. It also addresses a few errors and challenges while using such algorithms in real-world problems. The paper also discusses suggestions conveying researchers on model design, medical experts, and policymakers in the current situation while tackling the Covid-19 pandemic and ahead.
    Conclusion: The ongoing development in AI and ML has significantly improved treatment, medication, screening, prediction, forecasting, contact tracing, and drug/vaccine development process for the Covid-19 pandemic and reduce the human intervention in medical practice. However, most of the models are not deployed enough to show their real-world operation, but they are still up to the mark to tackle the SARS-CoV-2 epidemic.
    Keywords covid19
    Language English
    Publishing date 2020-06-25
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2020.110059
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  2. Article: Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review

    Lalmuanawma, Samuel / Hussain, Jamal / Chhakchhuak, Lalrinfela

    Chaos Solitons Fractals

    Abstract: ... pandemic. The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application ... in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and ... while tackling the Covid-19 pandemic and ahead. Conclusion: The ongoing development in AI and ML has ...

    Abstract Background and objective: During the recent global urgency, scientists, clinicians, and healthcare experts around the globe keep on searching for a new technology to support in tackling the Covid-19 pandemic. The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application on the previous epidemic encourage researchers by giving a new angle to fight against the novel Coronavirus outbreak. This paper aims to comprehensively review the role of AI and ML as one significant method in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and its related epidemic. Method: A selective assessment of information on the research article was executed on the databases related to the application of ML and AI technology on Covid-19. Rapid and critical analysis of the three crucial parameters, i.e., abstract, methodology, and the conclusion was done to relate to the model's possibilities for tackling the SARS-CoV-2 epidemic. Result: This paper addresses on recent studies that apply ML and AI technology towards augmenting the researchers on multiple angles. It also addresses a few errors and challenges while using such algorithms in real-world problems. The paper also discusses suggestions conveying researchers on model design, medical experts, and policymakers in the current situation while tackling the Covid-19 pandemic and ahead. Conclusion: The ongoing development in AI and ML has significantly improved treatment, medication, screening, prediction, forecasting, contact tracing, and drug/vaccine development process for the Covid-19 pandemic and reduce the human intervention in medical practice. However, most of the models are not deployed enough to show their real-world operation, but they are still up to the mark to tackle the SARS-CoV-2 epidemic.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #614269
    Database COVID19

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  3. Article ; Online: Artificial Intelligence (AI) applications for COVID-19 pandemic.

    Vaishya, Raju / Javaid, Mohd / Khan, Ibrahim Haleem / Haleem, Abid

    Diabetes & metabolic syndrome

    2020  Volume 14, Issue 4, Page(s) 337–339

    Abstract: ... Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Machine Learning to fight and look ahead against ... Coronavirus and Artificial Intelligence or AI. Collected the latest information regarding AI for COVID-19 ... review of the literature is done on the database of Pubmed, Scopus and Google Scholar using the keyword of COVID-19 or ...

    Abstract Background and aims: Healthcare delivery requires the support of new technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Machine Learning to fight and look ahead against the new diseases. We aim to review the role of AI as a decisive technology to analyze, prepare us for prevention and fight with COVID-19 (Coronavirus) and other pandemics.
    Methods: The rapid review of the literature is done on the database of Pubmed, Scopus and Google Scholar using the keyword of COVID-19 or Coronavirus and Artificial Intelligence or AI. Collected the latest information regarding AI for COVID-19, then analyzed the same to identify its possible application for this disease.
    Results: We have identified seven significant applications of AI for COVID-19 pandemic. This technology plays an important role to detect the cluster of cases and to predict where this virus will affect in future by collecting and analyzing all previous data.
    Conclusions: Healthcare organizations are in an urgent need for decision-making technologies to handle this virus and help them in getting proper suggestions in real-time to avoid its spread. AI works in a proficient way to mimic like human intelligence. It may also play a vital role in understanding and suggesting the development of a vaccine for COVID-19. This result-driven technology is used for proper screening, analyzing, prediction and tracking of current patients and likely future patients. The significant applications are applied to tracks data of confirmed, recovered and death cases.
    MeSH term(s) Artificial Intelligence ; Betacoronavirus/immunology ; COVID-19 ; COVID-19 Vaccines ; Coronavirus Infections/drug therapy ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Delivery of Health Care/trends ; Health Personnel ; Humans ; Pandemics/prevention & control ; Pneumonia, Viral/drug therapy ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; PubMed ; SARS-CoV-2 ; Viral Vaccines ; Workload ; COVID-19 Drug Treatment
    Chemical Substances COVID-19 Vaccines ; Viral Vaccines
    Keywords covid19
    Language English
    Publishing date 2020-04-14
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 2273766-2
    ISSN 1878-0334 ; 1871-4021
    ISSN (online) 1878-0334
    ISSN 1871-4021
    DOI 10.1016/j.dsx.2020.04.012
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Artificial Intelligence (AI) applications for COVID-19 pandemic

    Vaishya, Raju / Javaid, Mohd / Khan, Ibrahim Haleem / Haleem, Abid

    reponame:Expeditio Repositorio Institucional UJTL ; instname:Universidad de Bogotá Jorge Tadeo Lozano

    2020  

    Abstract: ... Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Machine Learning to fight and look ahead against ... Coronavirus and Artificial Intelligence or AI. Collected the latest information regarding AI for COVID-19 ... review of the literature is done on the database of Pubmed, Scopus and Google Scholar using the keyword of COVID-19 or ...

    Abstract Background and aims Healthcare delivery requires the support of new technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Machine Learning to fight and look ahead against the new diseases. We aim to review the role of AI as a decisive technology to analyze, prepare us for prevention and fight with COVID-19 (Coronavirus) and other pandemics. Methods The rapid review of the literature is done on the database of Pubmed, Scopus and Google Scholar using the keyword of COVID-19 or Coronavirus and Artificial Intelligence or AI. Collected the latest information regarding AI for COVID-19, then analyzed the same to identify its possible application for this disease. Results We have identified seven significant applications of AI for COVID-19 pandemic. This technology plays an important role to detect the cluster of cases and to predict where this virus will affect in future by collecting and analyzing all previous data. Conclusions Healthcare organizations are in an urgent need for decision-making technologies to handle this virus and help them in getting proper suggestions in real-time to avoid its spread. AI works in a proficient way to mimic like human intelligence. It may also play a vital role in understanding and suggesting the development of a vaccine for COVID-19. This result-driven technology is used for proper screening, analyzing, prediction and tracking of current patients and likely future patients. The significant applications are applied to tracks data of confirmed, recovered and death cases.
    Keywords Inteligencia artificial ; Síndrome respiratorio agudo grave ; COVID-19 ; SARS-CoV-2 ; Coronavirus ; Artificial Intelligence (AI) ; AI Applications ; Pandemic ; covid19
    Publisher Diabetes & Metabolic Syndrome: Clinical Research & Reviews
    Publishing country co
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic.

    Alhasan, Mustafa / Hasaneen, Mohamed

    Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

    2021  Volume 91, Page(s) 101933

    Abstract: ... challenges of artificial intelligence during COVID-19 pandemic. The paper applied systematic review approach ... of modern healthcare technologies and Artificial Intelligence (AI) during COVID-19 crisis, define ... COVID-19 responses using techniques like machine learning. Technology could be an endless system ...

    Abstract The advancement of technology remained an immersive interest for humankind throughout the past decades. Tech enterprises offered a stream of innovation to address the universal healthcare concerns. The novel coronavirus holds a substantial foothold of planet earth which is combatted by digital interventions across afflicted geographical boundaries and territories. This study aims to explore the trends of modern healthcare technologies and Artificial Intelligence (AI) during COVID-19 crisis, define the concepts and clinical role of AI in the mitigation of COVID-19, investigate and correlate the efficacy of AI-enabled technology in medical imaging during COVID-19 and determine advantages, drawbacks, and challenges of artificial intelligence during COVID-19 pandemic. The paper applied systematic review approach using a deliberated research protocol and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart. Digital technologies can coordinate COVID-19 responses in a cascade fashion that extends from the clinical care facility to the exterior of the pending viral epicenter. With cases of healthcare robotics, aerial drones, and the internet of things as evidentiary examples. PCR tests and medical imaging are the frontier diagnostics of COVID-19. Computed tomography helped to correct the accuracy variation of PCR tests at a clinical sensitivity of 98 %. Artificial intelligence can enable autonomous COVID-19 responses using techniques like machine learning. Technology could be an endless system of innovation and opportunities when sourced effectively. Scientists can utilize technology to resolve global concerns challenging the history of tangible possibility. Digital interventions have enhanced the responses to COVID-19, magnified the role of medical imaging amid the COVID-19 crisis and have exposed healthcare professionals to the opportunity of contactless care.
    MeSH term(s) Artificial Intelligence ; COVID-19 ; Digital Technology ; Machine Learning ; Pandemics ; SARS-CoV-2
    Language English
    Publishing date 2021-05-15
    Publishing country United States
    Document type Journal Article ; Systematic Review
    ZDB-ID 639451-6
    ISSN 1879-0771 ; 0895-6111
    ISSN (online) 1879-0771
    ISSN 0895-6111
    DOI 10.1016/j.compmedimag.2021.101933
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1323: Show issues Location:
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    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article: Mapping the Landscape of Artificial Intelligence Applications against COVID-19

    Joseph Bullock / Alexandra Luccioni / Katherine Pham Hoffmann / Cynthia Lam Sin Nga / Miguel Luengo-Oroz

    Abstract: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic ... an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle ... many aspects of the COVID-19 crisis at different scales including molecular, clinical, and societal ...

    Abstract COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of April 23, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales including molecular, clinical, and societal applications. We also review datasets, tools, and resources needed to facilitate AI research. Finally, we discuss strategic considerations related to the operational implementation of projects, multidisciplinary partnerships, and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.
    Keywords covid19
    Publisher arxiv
    Document type Article
    Database COVID19

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  7. Article: Mapping the Landscape of Artificial Intelligence Applications against COVID-19

    Bullock, Joseph / Luccioni, Alexandra / Pham, Katherine Hoffmann / Lam, Cynthia Sin Nga / Luengo-Oroz, Miguel

    Abstract: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic ... an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle ... many aspects of the COVID-19 crisis at different scales including molecular, clinical, and societal ...

    Abstract COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of April 23, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales including molecular, clinical, and societal applications. We also review datasets, tools, and resources needed to facilitate AI research. Finally, we discuss strategic considerations related to the operational implementation of projects, multidisciplinary partnerships, and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  8. Book ; Online: Mapping the Landscape of Artificial Intelligence Applications against COVID-19

    Bullock, Joseph / Luccioni, Alexandra / Pham, Katherine Hoffmann / Lam, Cynthia Sin Nga / Luengo-Oroz, Miguel

    2020  

    Abstract: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic ... we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence ... data sources. We also review datasets, tools, and resources needed to facilitate Artificial Intelligence ...

    Abstract COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis. We have identified applications that address challenges posed by COVID-19 at different scales, including: molecular, by identifying new or existing drugs for treatment; clinical, by supporting diagnosis and evaluating prognosis based on medical imaging and non-invasive measures; and societal, by tracking both the epidemic and the accompanying infodemic using multiple data sources. We also review datasets, tools, and resources needed to facilitate Artificial Intelligence research, and discuss strategic considerations related to the operational implementation of multidisciplinary partnerships and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.

    Comment: 39 pages, v2: much larger to reflect the significant increase in the size of the body of literature, v3: uploaded with JAIR page numbers and references
    Keywords Computer Science - Computers and Society ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Computer Science - Social and Information Networks
    Subject code 401
    Publishing date 2020-03-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining.

    Rodríguez-Rodríguez, Ignacio / Rodríguez, José-Víctor / Shirvanizadeh, Niloofar / Ortiz, Andrés / Pardo-Quiles, Domingo-Javier

    International journal of environmental research and public health

    2021  Volume 18, Issue 16

    Abstract: ... of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most ... to obtain an overall view of the different applications of AI to the management of COVID-19 and ... to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose ...

    Abstract The COVID-19 pandemic has wreaked havoc in every country in the world, with serious health-related, economic, and social consequences. Since its outbreak in March 2020, many researchers from different fields have joined forces to provide a wide range of solutions, and the support for this work from artificial intelligence (AI) and other emerging concepts linked to intelligent data analysis has been decisive. The enormous amount of research and the high number of publications during this period makes it difficult to obtain an overall view of the different applications of AI to the management of COVID-19 and an understanding of how research in this field has been evolving. Therefore, in this paper, we carry out a scientometric analysis of this area supported by text mining, including a review of 18,955 publications related to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose, we used VOSviewer software, which was developed by researchers at Leiden University in the Netherlands. This allowed us to examine the exponential growth in research on this issue and its distribution by country, and to highlight the clear hegemony of the United States (USA) and China in this respect. We used an automatic process to extract topics of research interest and observed that the most important current lines of research focused on patient-based solutions. We also identified the most relevant journals in terms of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most influential authors by means of an analysis of citations and co-citations. This study provides an overview of the current status of research on the application of AI to the pandemic.
    MeSH term(s) Artificial Intelligence ; Big Data ; COVID-19 ; Data Mining ; Humans ; Internet of Things ; Machine Learning ; Pandemics ; SARS-CoV-2
    Language English
    Publishing date 2021-08-13
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2175195-X
    ISSN 1660-4601 ; 1661-7827
    ISSN (online) 1660-4601
    ISSN 1661-7827
    DOI 10.3390/ijerph18168578
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  10. Article ; Online: Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic

    Lalmuanawma, Samuel / Hussain, Jamal / Chhakchhuak, Lalrinfela

    Chaos, Solitons & Fractals

    A review

    2020  Volume 139, Page(s) 110059

    Keywords General Mathematics ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2020.110059
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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