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  1. Article ; Online: Application of cognitive Internet of Medical Things for COVID-19 pandemic.

    Swayamsiddha, Swati / Mohanty, Chandana

    Diabetes & metabolic syndrome

    2020  Volume 14, Issue 5, Page(s) 911–915

    Abstract: Background and aim: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based ... ...

    Abstract Background and aim: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management.
    Methods: An extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms "COVID-19" and "Cognitive IoT" or "Corona virus" and "IoMT". The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas.
    Results: This review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified.
    Conclusions: CIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others.
    MeSH term(s) Betacoronavirus/isolation & purification ; COVID-19 ; Cognition ; Coronavirus Infections/diagnosis ; Coronavirus Infections/prevention & control ; Coronavirus Infections/transmission ; Coronavirus Infections/virology ; Delivery of Health Care/standards ; Humans ; Internet of Things/standards ; Internet of Things/statistics & numerical data ; Pandemics/prevention & control ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/transmission ; Pneumonia, Viral/virology ; SARS-CoV-2 ; Telemedicine/methods
    Keywords covid19
    Language English
    Publishing date 2020-06-11
    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.2020.06.014
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: The prospective of Artificial Intelligence in COVID-19 Pandemic.

    Swayamsiddha, Swati / Prashant, Kumar / Shaw, Devansh / Mohanty, Chandana

    Health and technology

    2021  Volume 11, Issue 6, Page(s) 1311–1320

    Abstract: Coronavirus disease 2019 (COVID-19) is a major threat throughout the world. The latest advancements in the field of computational techniques based on Artificial Intelligence (AI), Machine Learning (ML) and Big Data can help in detecting, monitoring and ... ...

    Abstract Coronavirus disease 2019 (COVID-19) is a major threat throughout the world. The latest advancements in the field of computational techniques based on Artificial Intelligence (AI), Machine Learning (ML) and Big Data can help in detecting, monitoring and forecasting the severity of the COVID-19 pandemic. We aim to review the detection of the COVID-19 pandemic empowered by AI, major implications, challenges and the future of smart health care at a glance. The AI plays a pioneering role in rapid and improved detection of the disease. It helps in modeling the disease activity and predicting the severity for better decision making and preparedness by healthcare authorities and policymakers. It is a promising technology for automatic and fully transparent monitoring system to track and treat the patients remotely without spreading the virus to others. The future application areas of AI-based healthcare are also identified. The role of AI in tackling the COVID-19 pandemic is reviewed in this paper. AI proves beneficial in early detection with improved results. It also provides solution for contact tracing, prediction, drug development thus reducing the workload of medical industry.
    Language English
    Publishing date 2021-09-28
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 2581463-1
    ISSN 2190-7196 ; 2190-7188
    ISSN (online) 2190-7196
    ISSN 2190-7188
    DOI 10.1007/s12553-021-00601-2
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  3. Article ; Online: Application of cognitive Internet of Medical Things for COVID-19 pandemic

    Swayamsiddha, Swati / Mohanty, Chandana

    Diabetes & Metabolic Syndrome: Clinical Research & Reviews

    2020  Volume 14, Issue 5, Page(s) 911–915

    Keywords Internal Medicine ; Endocrinology, Diabetes and Metabolism ; General Medicine ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2273766-2
    ISSN 1878-0334 ; 1871-4021
    ISSN (online) 1878-0334
    ISSN 1871-4021
    DOI 10.1016/j.dsx.2020.06.014
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Modern computational intelligence based drug repurposing for diabetes epidemic.

    Mohanty, Sweta / Rashid, Md Harun Al / Mohanty, Chandana / Swayamsiddha, Swati

    Diabetes & metabolic syndrome

    2021  Volume 15, Issue 4, Page(s) 102180

    Abstract: Background and aim: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.: Methods: ... ...

    Abstract Background and aim: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.
    Methods: Recent literature were studied and analyzed from various sources such as Scopus, PubMed, and IEEE Xplore databases.
    Results: Drugs like Niclosamideethanolamine, Methazolamide, Diacerein, Berberine, Clobetasol, etc. with possibility of repurposing to curb diabetes can be potential late-stage clinical candidates, providing access to information on pharmacology, formulation, and probable toxicity if any.
    Conclusions: With collaboration of artificial intelligence (AI) with pharmacology, the efficiency of drug repurposing can improve significantly.
    MeSH term(s) Artificial Intelligence ; Diabetes Mellitus, Type 2/drug therapy ; Drug Discovery ; Drug Repositioning ; Humans ; Hypoglycemic Agents/pharmacology ; Internet ; Knowledge Bases
    Chemical Substances Hypoglycemic Agents
    Language English
    Publishing date 2021-06-18
    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.2021.06.017
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Application of cognitive Internet of Medical Things for COVID-19 pandemic

    Swayamsiddha, Swati / Mohanty, Chandana

    Diabetes Metab Syndr

    Abstract: BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT ...

    Abstract BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management. METHODS: An extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms "COVID-19" and "Cognitive IoT" or "Corona virus" and "IoMT". The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas. RESULTS: This review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified. CONCLUSIONS: CIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #593506
    Database COVID19

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  6. Article: Reporting cell planning-based cellular mobility management using a Binary Artificial Bat algorithm.

    Swayamsiddha, Swati / Prateek / Singh, Sudhansu Sekhar / Parija, Smita / Pratihar, Dilip Kumar

    Heliyon

    2019  Volume 5, Issue 3, Page(s) e01276

    Abstract: This paper attempts to present a novel application of Binary Artificial Bat algorithm for more effective location management in cellular networks. The location management is a mobility management task, which involves tracking of the mobile stations to ... ...

    Abstract This paper attempts to present a novel application of Binary Artificial Bat algorithm for more effective location management in cellular networks. The location management is a mobility management task, which involves tracking of the mobile stations to locate their exact positions so that an incoming call or data can be routed to the intended mobile user. The location management cost comprises of the costs incurred by two processes, namely location registration and location search. This work focuses on network cost optimization, using Binary Artificial Bat algorithm for reporting cell planning strategy, which has not been reported yet. Results of the proposed algorithm have been compared with that of Binary Particle Swarm Optimization (BPSO) and Binary Differential Evolution (BDE) for some reference and realistic networks. The proposed approach is found to perform as good as other state-of-art techniques reported in the literature in terms of accuracy in solution, but it shows perceptible improvement in convergence speed.
    Language English
    Publishing date 2019-03-07
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2019.e01276
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Application of Artificial Intelligence in COVID-19 drug repurposing.

    Mohanty, Sweta / Harun Ai Rashid, Md / Mridul, Mayank / Mohanty, Chandana / Swayamsiddha, Swati

    Diabetes & metabolic syndrome

    2020  Volume 14, Issue 5, Page(s) 1027–1031

    Abstract: Background and aim: COVID-19 outbreak has created havoc and a quick cure for the disease will be a therapeutic medicine that has usage history in patients to resolve the current pandemic. With technological advancements in Artificial Intelligence (AI) ... ...

    Abstract Background and aim: COVID-19 outbreak has created havoc and a quick cure for the disease will be a therapeutic medicine that has usage history in patients to resolve the current pandemic. With technological advancements in Artificial Intelligence (AI) coupled with increased computational power, the AI-empowered drug repurposing can prove beneficial in the COVID-19 scenario.
    Methods: The recent literature is studied and analyzed from various sources such as Scopus, Google Scholar, PubMed, and IEEE Xplore databases. The search terms used are 'COVID-19', ' AI ', and 'Drug Repurposing'.
    Results: AI is implemented in the field design through the generation of the learning-prediction model and performs a quick virtual screening to accurately display the output. With a drug-repositioning strategy, AI can quickly detect drugs that can fight against emerging diseases such as COVID-19. This technology has the potential to improve the drug discovery, planning, treatment, and reported outcomes of the COVID-19 patient, being an evidence-based medical tool.
    Conclusions: Thus, there are chances that the application of the AI approach in drug discovery is feasible. With prior usage experiences in patients, few of the old drugs, if shown active against SARS-CoV-2, can be readily applied to treat the COVID-19 patients. With the collaboration of AI with pharmacology, the efficiency of drug repurposing can improve significantly.
    MeSH term(s) Artificial Intelligence ; Betacoronavirus/drug effects ; COVID-19 ; Coronavirus Infections/drug therapy ; Coronavirus Infections/virology ; Drug Repositioning/methods ; Humans ; Pandemics ; Pneumonia, Viral/drug therapy ; Pneumonia, Viral/virology ; SARS-CoV-2 ; COVID-19 Drug Treatment
    Keywords covid19
    Language English
    Publishing date 2020-07-03
    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.2020.06.068
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Application of Artificial Intelligence in COVID-19 drug repurposing

    Mohanty, Sweta / Harun AI Rashid, Md / Mridul, Mayank / Mohanty, Chandana / Swayamsiddha, Swati

    Diabetes & Metabolic Syndrome: Clinical Research & Reviews

    2020  Volume 14, Issue 5, Page(s) 1027–1031

    Keywords Internal Medicine ; Endocrinology, Diabetes and Metabolism ; General Medicine ; covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2273766-2
    ISSN 1878-0334 ; 1871-4021
    ISSN (online) 1878-0334
    ISSN 1871-4021
    DOI 10.1016/j.dsx.2020.06.068
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Order via subito

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  9. Article ; Online: Reporting cell planning-based cellular mobility management using a Binary Artificial Bat algorithm

    Swati Swayamsiddha / Prateek / Sudhansu Sekhar Singh / Smita Parija / Dilip Kumar Pratihar

    Heliyon, Vol 5, Iss 3, Pp e01276- (2019)

    2019  

    Abstract: This paper attempts to present a novel application of Binary Artificial Bat algorithm for more effective location management in cellular networks. The location management is a mobility management task, which involves tracking of the mobile stations to ... ...

    Abstract This paper attempts to present a novel application of Binary Artificial Bat algorithm for more effective location management in cellular networks. The location management is a mobility management task, which involves tracking of the mobile stations to locate their exact positions so that an incoming call or data can be routed to the intended mobile user. The location management cost comprises of the costs incurred by two processes, namely location registration and location search. This work focuses on network cost optimization, using Binary Artificial Bat algorithm for reporting cell planning strategy, which has not been reported yet. Results of the proposed algorithm have been compared with that of Binary Particle Swarm Optimization (BPSO) and Binary Differential Evolution (BDE) for some reference and realistic networks. The proposed approach is found to perform as good as other state-of-art techniques reported in the literature in terms of accuracy in solution, but it shows perceptible improvement in convergence speed.
    Keywords Computer science ; Electrical engineering ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Subject code 006
    Language English
    Publishing date 2019-03-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: Application of Artificial Intelligence in COVID-19 drug repurposing

    Mohanty, Sweta / Harun Ai Rashid, Md / Mridul, Mayank / Mohanty, Chandana / Swayamsiddha, Swati

    Diabetes Metab Syndr

    Abstract: BACKGROUND AND AIM: COVID-19 outbreak has created havoc and a quick cure for the disease will be a therapeutic medicine that has usage history in patients to resolve the current pandemic. With technological advancements in Artificial Intelligence (AI) ... ...

    Abstract BACKGROUND AND AIM: COVID-19 outbreak has created havoc and a quick cure for the disease will be a therapeutic medicine that has usage history in patients to resolve the current pandemic. With technological advancements in Artificial Intelligence (AI) coupled with increased computational power, the AI-empowered drug repurposing can prove beneficial in the COVID-19 scenario. METHODS: The recent literature is studied and analyzed from various sources such as Scopus, Google Scholar, PubMed, and IEEE Xplore databases. The search terms used are 'COVID-19', ' AI ', and 'Drug Repurposing'. RESULTS: AI is implemented in the field design through the generation of the learning-prediction model and performs a quick virtual screening to accurately display the output. With a drug-repositioning strategy, AI can quickly detect drugs that can fight against emerging diseases such as COVID-19. This technology has the potential to improve the drug discovery, planning, treatment, and reported outcomes of the COVID-19 patient, being an evidence-based medical tool. CONCLUSIONS: Thus, there are chances that the application of the AI approach in drug discovery is feasible. With prior usage experiences in patients, few of the old drugs, if shown active against SARS-CoV-2, can be readily applied to treat the COVID-19 patients. With the collaboration of AI with pharmacology, the efficiency of drug repurposing can improve significantly.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #621859
    Database COVID19

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    Inter-library loan at ZB MED

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