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Data science advancements in pandemic and outbreak management - [electronic resource]
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Data science advancements in pandemic and outbreak management - [electronic resource]
상세정보
- 자료유형
- 전자책(국외)
- 미국국회도서관 청구기호
- RA648.5-.D38 2021
- 자관 청구기호
- 기본표목-개인명
- 표제와 책임표시사항
- Data science advancements in pandemic and outbreak management [electronic resource] / Eleana Asimakopoulou, Nik Bessis.
- 출판 정보
- Hershey, PA:Engineering Science Reference, an imprint of IGI Global[2021]
- 형태사항
- 1 online resource (xix, 255 pages) : color illustrations.
- 총서사항
- Advances in data mining and database management (ADMDM) book series
- 일반주기
- "Premier Reference Source" -- taken from front cover.
- 서지 등 주기
- Includes bibliographical references and index.
- 내용주기
- 완전내용Section 1. Overview of technologies for pandemic management. Chapter 1. A review of technologies in emergency medicine and sophisticated collective decision-making in the era of the fight against the pandemic ; Chapter 2. Overview of IoT and machine learning for e-healthcare in pandemics and health crises ; Chapter 3. Data analytics epidemic modelling and human dynamics approaches for pandemic outbreak -- Section 2. Data science practices in pandemic management. Chapter 4. The importance of big data metadata in crisis management ; Chapter 5. Pandemic management with social media analytics ; Chapter 6. Deep learning approaches in pandemic and disaster management ; Chapter 7. Information extraction from social media for epidemic models ; Chapter 8. Towards combating pandemic-related misinformation in social media -- Section 3. Technology-driven challenges and implications in pandemic management. Chapter 9. Ensuring food supply and security during localised lockdowns: an information and technology-based approach ; Chapter 10. Privacy-preserving pandemic monitoring ; Chapter 11. Strategies for upskilling in data science after the COVID 19 pandemic.
- 요약 등 주기
- 요약"This book demonstrates how strategies and state-of-the-art information technologies have and/or could be applied to serve as the vehicle to advance pandemic and outbreak management including revisiting and critically reviewing past and current approaches, identifying good and bad practices and further developing adaptation for future pandemics and outbreaks"--해제Provided by publisher.
- 주제명부출표목-일반주제명
- 주제명부출표목-일반주제명
- 주제명부출표목-일반주제명
- 부출표목-개인명
- 기타형태저록
- Print version Data science advancements in pandemic and outbreak management
- 총서부출표목-통일표제
- Advances in data mining and database management (ADMDM) book series.
- 전자적 위치 및 접속
- 링크정보보기
MARC
008230126s2021 ulka sb 001 kor■001on1224583387
■003OCoLC
■00520210709060300.9
■007cr
■010 ▼a 2020052952
■019 ▼a1243422233
■020 ▼a9781799867388▼qelectronic book
■020 ▼a1799867382▼qelectronic book
■020 ▼a9781799867395▼q(electronic bk.)
■020 ▼a1799867390▼q(electronic bk.)
■020 ▼z9781799867364▼qhardcover
■020 ▼z9781799867371▼qpaperback
■0247 ▼a10.4018/978-1-7998-6736-4▼2doi
■035 ▼a2898561▼b(N$T)
■035 ▼a(OCoLC)1224583387▼z(OCoLC)1243422233
■040 ▼aDLC▼beng▼erda▼cDLC▼dOCLCO▼dOCLCF▼dOCLCO▼dYDX▼dOCLCO▼dIGIGL▼dN$T
■042 ▼apcc
■049 ▼aMAIN
■05004▼aRA648.5▼b.D38 2021
■08200▼a614.40285▼223
■090 ▼a전자도서
■1001 ▼aAsimakopoulou, Eleana▼d1976-▼eeditor.
■24510▼aData science advancements in pandemic and outbreak management ▼h[electronic resource] /▼cEleana Asimakopoulou, Nik Bessis.
■264 1▼aHershey, PA▼bEngineering Science Reference, an imprint of IGI Global▼c[2021]
■300 ▼a1 online resource (xix, 255 pages)▼bcolor illustrations.
■336 ▼atext▼btxt▼2rdacontent
■337 ▼acomputer▼bc▼2rdamedia
■338 ▼aonline resource▼bcr▼2rdacarrier
■4901 ▼aAdvances in data mining and database management (ADMDM) book series
■500 ▼a"Premier Reference Source" -- taken from front cover.
■504 ▼aIncludes bibliographical references and index.
■5050 ▼aSection 1. Overview of technologies for pandemic management. Chapter 1. A review of technologies in emergency medicine and sophisticated collective decision-making in the era of the fight against the pandemic ; Chapter 2. Overview of IoT and machine learning for e-healthcare in pandemics and health crises ; Chapter 3. Data analytics epidemic modelling and human dynamics approaches for pandemic outbreak -- Section 2. Data science practices in pandemic management. Chapter 4. The importance of big data metadata in crisis management ; Chapter 5. Pandemic management with social media analytics ; Chapter 6. Deep learning approaches in pandemic and disaster management ; Chapter 7. Information extraction from social media for epidemic models ; Chapter 8. Towards combating pandemic-related misinformation in social media -- Section 3. Technology-driven challenges and implications in pandemic management. Chapter 9. Ensuring food supply and security during localised lockdowns: an information and technology-based approach ; Chapter 10. Privacy-preserving pandemic monitoring ; Chapter 11. Strategies for upskilling in data science after the COVID 19 pandemic.
■520 ▼a"This book demonstrates how strategies and state-of-the-art information technologies have and/or could be applied to serve as the vehicle to advance pandemic and outbreak management including revisiting and critically reviewing past and current approaches, identifying good and bad practices and further developing adaptation for future pandemics and outbreaks"--▼cProvided by publisher.
■588 ▼aDescription based on online resource; title from digital title page (viewed on April 01, 2021).
■590 ▼aAdded to collection customer.56279.3
■650 0▼aEpidemiology.
■650 0▼aEmergency management▼xInformation technology.
■650 7▼aEpidemiology.▼2fast▼0(OCoLC)fst00914091
■655 4▼aElectronic books.
■7001 ▼aBessis, Nik▼d1967-▼eeditor.
■77608▼iPrint version▼tData science advancements in pandemic and outbreak management▼dHershey, PA : Engineering Science Reference, [2021]▼z9781799867364▼w(DLC) 2020052951
■830 0▼aAdvances in data mining and database management (ADMDM) book series.
■85640▼3EBSCOhost▼uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2898561
■938 ▼aEBSCOhost▼bEBSC▼n2898561
■994 ▼a92▼bN$T
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