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Artificial Intelligence in Healthcare: Transitioning to Routine Clinical Care

  • Ketan Paranjape

    Research output: PhD ThesisPhD-Thesis - Research and graduation internal

    2071 Downloads (Pure)

    Abstract

    This thesis fills a knowledge gap in implementing AI for patient care by understanding the challenges with today’s algorithms, demonstrating the value of using AI techniques like machine learning on disease states like sepsis and oncology to identify patient populations who could benefit from certain interventions, understanding the challenges in implementing AI for laboratory medicine, developing a new medical curriculum to train healthcare staff in understanding and using AI, study the regulatory and policy work behind implementing AI by understanding challenges like explainability, blackbox, bias and ethics and demonstrate how you can deploy new technologiesI in healthcare to deliver better patient care, reduce cost of care and deliver accessible care.
    Original languageEnglish
    QualificationPhD
    Awarding Institution
    • Vrije Universiteit Amsterdam
    Supervisors/Advisors
    • Nanayakkara, Kurukula Don Prabath Wasantha Bernard, Supervisor, -
    • Kramer, Mark , Supervisor, -
    • Elbers, Paul, Co-supervisor, -
    Award date16 Sept 2022
    Place of PublicationAmsterdam
    Publisher
    Print ISBNs9789493278134
    Publication statusPublished - 16 Sept 2022

    Keywords

    • Artificial Intelligence, Sepsis, Oncology, Personalized Medicine, Machine Learning, Clinical Decision Support, Medical Education, Policy and Regulation

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