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    1. Naturvetenskap och teknik
    2. Matematik och naturvetenskap
    3. Biologi
    4. Biovetenskap

    Human-AI-Cognitive Intelligence Software, System, and Services for Quality Assurance

    Theories and Methods with Systems Thinking for Behaviour Change in the Medical Decision-Making Pathway

    AvPantea Keikhosrokiani

    Häftad, Engelska, 2027

    1 573 kr

    Kommande

    Beskrivning

    Habit-based Behavior Change Medical Information Support System and Artificial Intelligence: Theories, Methods, and Data Analytics Approach provides a guideline to design and implement Habit-based Behavior Change Support Systems (HBCSS) which can change patient’s unhealthy habits to prevent the development of diseases. It presents theories, methods, management, and data analytics approach required to design, implement, and prescribe the use of HBCSS for several diseases’ management.It discusses topics such as theories of behavior change, ontologies and knowledge management, data mining, privacy and security, descriptive and prescription analytics. In addition, it discusses how to measure habit-change, future directions of the field, and case studies based on real-world examples.It is a valuable resource for clinicians, researchers, students, and member of the biomedical and medical fields who want to learn more about the use of medical systems to improve patients’ health.

    • Discusses how habit-change features can be added to medical information systems to change patient’s unhealthy habits
    • Describes the habit-change life cycle and framework so that readers can develop their own system
    • Outlines how data analytics features are used to diagnose and predict unhealthy habits and prescribe changes to improve overall health of patients

    Produktinformation

    • Utgivningsdatum:2027-01-01
    • Mått:191 x 235 x undefined mm
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:400
    • Förlag:Elsevier Science
    • ISBN:9780443137594

    Utforska kategorier

    • Biovetenskap inom Naturvetenskap och teknik

    Mer om författaren

    Pantea Keikhosrokiani is a Senior Lecturer at the School of Computer Sciences, Universiti Sains Malaysia (USM; Penang, Malaysia). She was a teaching fellow at the National Advanced IPv6 Centre of Excellence (Nav6), USM. She has received her PhD in Service System Engineering, Information System, and her master’s degree in information technology from the School of Computer Sciences, USM. She has been graduated in Bachelor of Science in Electrical Engineering Electronics. Her articles have been published in distinguished edited books and journals including Elsevier (Telematics & Informatics), Springer (Cognition, Technology, & Work), Taylors and Francis and IGI global, and have been indexed by ISI, Scopus and PubMed. Her recent book is published by Elsevier entitled Perspectives in The Development of Mobile Medical Information Systems: Life Cycle, Management, Methodological Approach and Application. Her areas of interest for research and teaching are Information Systems Development, Behavior-change support systems, Database Systems, Health and Medical Informatics, Business Informatics, Location-Based Mobile Applications, Big Data, and Technopreneurship.

    Innehållsförteckning

    • Section 1: Introduction to Habit-based Behavior Change Support Systems (HBCSS)1. Theories for Habit-based Behavior Change Support Systems (HBCSS)2. Methodologies for Habit-based Behavior Change Support Systems (HBCSS)3. Management of Habit-based Behavior Change Support Systems (HBCSS)4. Features of Habit-based Behavior Change Support Systems (HBCSS)Section 2: Habit-change Life Cycles for Developing HBCSS5. Requirements for HBCSS6. Bad Habit Identification7. Breaking Bad Habits8. New Habit Formation9. Measuring Habit-Change10. Evaluating Habit-Change11. Development of HBCSS12. Securing HBCSSSection 3: Measuring Habit-Change in Habit-based Behavior Change Support Systems (HBCSS) using Data Analytics13. Descriptive Analytics for Habit-Change14. Classification for Habit-Change15. Clustering for Habit-Change16. Prediction for Habit-Change17. Prescription Analytics for HBCSS18. Databases for HBCSS19. Conclusion and Future Direction20. Case Studies