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020 _a9789811573170
024 7 _a10.1007/978-981-15-7317-0
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aR859.7.A78
_b2021 EB
245 0 0 _aApplications of Artificial Intelligence in COVID-19
_cedited by Sachi Nandan Mohanty, Shailendra K. Saxena, Suneeta Satpathy, Jyotir Moy Chatterjee.
250 _aFirst edition 2021
264 1 _aSingapore
_bSpringer International Publishing
_c2021
300 _a1 recurso en línea (XX, 595 páginas)
_b216 ilustraciones, 147 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aArchivo de texto
_bPDF
490 0 _aMedical Virology: From Pathogenesis to Disease Control
_x2662-9828
490 0 _aBiomedical and Life Sciences (SpringerNature-11642)
490 0 _aBiomedical and Life Sciences (R0) (SpringerNature-43708)
505 0 _aChapter 1.Comprehensive Claims of AI for Healthcare Applications-Coherence towards COVID-19 -- Chapter 2. Artificial Intelligence based systems for combating COVID-19 -- Chapter 3. Artificial intelligence mediated medical diagnosis of COVID-19 -- Chapter 4. AI combined with medical imaging enables rapid diagnosis for COVID-19 -- Chapter 5. Role of Artificial Intelligence in COVID-19 prediction based on Statistical Methods -- Chapter 6. Data Driven symptom Analysis and Location Prediction Model for Clinical Health Data Processing and Knowledgebase Development for COVID 19 -- Chapter 7. A decision support System using Rule based Expert System For COVID -19 Prediction and Diagnosis -- Chapter 8. A Predictive Mechanism to Intimate the Danger of Infection via nCOVID-19 through Unsupervised Learning -- Chapter 9. AI-enabled prognosis technologies for SARS Co-2. Chapter 10. Intelligent agent Based Case Base Reasoning Systems Build Knowledge Representation in COVID-19 analysis of Recovery, Infectious Patients -- Chapter 11. Epidemic Analysis of COVID 19 Using Machine Learning -- Chapter 12. Machine learning application in COVID-19 drug development -- Chapter 13. COVID 19 Epidemic Analysis Using Linear and Polynomial Regression Approach -- Chapter 14. Prediction & Analysis of outbreak of COVID-19 Pandemic Using Machine Learning -- Chapter 15. Predictive Risk Analysis by using Machine Learning during Covid-19 -- Chapter 16. Analysis and Validation of Risk Prediction by Stochastic Gradient Boosting Along With Recursive Feature Elimination for COVID-19 -- Chapter 17. Artificial intelligence in mental healthcare during COVID-19 pandemic -- Chapter 18. Effect of Covid-19 on Autism Spectrum Disorder: Prognosis, diagnosis and therapeutics based On AI -- Chapter 19. Use of mobile phone apps for contact tracing to control the COVID-19 pandemic: A Literature Review -- Chapter 20. Role of IoT and Social Networking in Mental Healthcare of Transgender Community in Covid-19 Pandemic -- Chapter 21. TECHNOLOGY ACCEPTANCE AND USE OF IOT DURING COVID 19 PANDEMIC-CASE STUDY OF HEALTH SECTOR IN INDIA. Chapter 22. Artificial Intelligence - The Strategies used in COVID-19 for Diagnosis -- Chapter 23. Impact of Isolation and Quarantine on Covid-19 Patients and Potential Role of Technology in Mitigation -- Chapter 24. Impact of loneliness and Quarantine on COVID-19 patients with artificial intelligence applications -- Chapter 25. Can Technology fight the loneliness Lockdown: A study of factors Affecting Loneliness in NCR during COVID 19 -- Chapter 26. Psycho-economic Impact of Obligatory Job Switching during Covid-19 Pandemic: A Study of Hawkers in Bhubaneswar (India) -- Chapter 27. AI's Role in Essential Commodities during a Pandemic Situation -- Chapter 28.Impact of COVID-19 on Manufacturing and Operational Ecosystem in India -- Chapter 29. Impact of Repatriated Migrants on the Production Possibility of Agricultural Sector owing to Covid: A Study on the basis of Inferential Statistics -- Chapter 30. Nicotine in Covid-19: Friend or Foe";? -- Chapter 31. Artificial Intelligence in Covid'19: Application and Legal Conundrums.
520 3 _aThe book examines the role of artificial intelligence during the COVID-19 pandemic, including its application in i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments, and cures, and vi) social control. It explores the use of artificial intelligence in the context of population screening and assessing infection risks, and presents mathematical models for epidemic prediction of COVID-19. Furthermore, the book discusses artificial intelligence-mediated diagnosis, and how machine learning can help in the development of drugs to treat the disease. Lastly, it analyzes various artificial intelligence-based models to improve the critical care of COVID-19 patients.
988 _aSpringer_BiomedLife_2021
650 7 _2embne
_9421371
_aInteligencia artificial en medicina
650 7 _2embne
_aCOVID-19
_9683668
700 1 _aNandan Mohanty, Sachi.
_eeditor literario
_0(orcid)0000-0002-4939-0797
_1https://orcid.org/0000-0002-4939-0797
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSaxena, Shailendra K.
_eeditor literario
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSatpathy, Suneeta.
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aChatterjee, Jyotir Moy.
_eeditor literario
_0(orcid)0000-0003-2527-916X
_1https://orcid.org/0000-0003-2527-916X
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
776 0 8 _iPrinted edition:
_z9789811573163
776 0 8 _iPrinted edition:
_z9789811573187
776 0 8 _iPrinted edition:
_z9789811573194
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-15-7317-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
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998 _b01/2022
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