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    <title>Data Science and Artificial Intelligence for Digital Healthcare</title>
    <subTitle>Communications Technologies for Epidemic Models</subTitle>
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    <namePart>Singh, Pradeep Kumar.</namePart>
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    <namePart>Trovati, Marcello.</namePart>
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    <namePart>Murtagh, Fionn.</namePart>
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    <namePart>Atiquzzaman, Mohammed.</namePart>
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    <namePart>Farid, Mohsen.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>XI, 284 p. 114 illus., 97 illus. in color. online resource.</extent>
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  <abstract>This book explores current research and development in the area of digital healthcare using recent technologies such as data science and artificial intelligence. The authors discuss how data science, AI, and mobile technologies provide the fundamental backbone to digital healthcare, presenting each technology separately as well covering integrated solutions. The book also focuses on the integration of different multi-disciplinary approaches along with examples and case studies. In order to identify the challenges with security and privacy issues, relevant block chain technologies are identified and discussed. Social aspects related to digital solutions and platforms for healthcare are also discussed and analyzed. The book aims to present high quality, technical contributions in the field of mobile digital healthcare using technologies such as AI, deep learning, IoT and distributed cloud computing.</abstract>
  <tableOfContents>Introduction -- PART-1: PANDEMIC MODELS USING DATA SCIENCE AND ARTIFICIAL INTELLIGENCE -- Data science for preventive care -- Artificial intelligence and deep learning for epidemic models -- Data analytics and cognitive computing for mobile digital health -- Multimedia big data for digital health and related topics -- PART-2: ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN HEALTHCARE 4.0 -- Artificial intelligence and deep learning for clinical diagnosis -- AI- supported healthcare in IoT-cloud based platforms -- AI- empowered big data analytics and cognitive computing for smart health monitoring -- AI and ML techniques for intelligent mobile digital health solutions -- PART-3: IoT, EDGE/FOG AND CLOUD IN DIGITAL HEALTHCARE -- Wireless sensor networks &amp; IoT for digital health -- Internet of Medical Things (IoMT) in digital health -- Advanced AIIoT convergent services, systems, infrastructure, and techniques for healthcare -- AI-supported IoT data analytics for smart healthcare -- Fog/edge Computing for digital health -- PART-4: DISTRIBUTED LEDGER AND SECURITY SOLUTIONS FOR DIGITAL HEALTHCARE RECORDS -- Block chain based electronic health record -- Blockchain for digital health Security -- Cyber Physical Systems for digital healthcare records -- Cryptography and other security solutions for the digital healthcare -- PART-5: INNOVATIVE SOLUTIONS IN MOBILE DIGITAL HEALTHCARE -- Computer aided detection and diagnosis -- Elderly smart health monitoring environments and related topics -- Conclusion.</tableOfContents>
  <note type="statement of responsibility">edited by Pradeep Kumar Singh, Marcello Trovati, Fionn Murtagh, Mohammed Atiquzzaman, Mohsen Farid.</note>
  <subject authority="lcsh">
    <topic>Telecommunication</topic>
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    <topic>Cooperating objects (Computer systems)</topic>
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    <topic>Data processing</topic>
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    <topic>Cyber-Physical Systems</topic>
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    <topic>Health Informatics</topic>
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  <subject>
    <topic>Artificial Intelligence</topic>
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    <topic>Data Science</topic>
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  <identifier type="isbn">9783031568183</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-56818-3</identifier>
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