Opportunities and Challenges of Swarm AI for Decentralized Clinical Research
Keywords:swarm learning, blockchain in healthcare, swarm AI and drug development, federated vs swarm learning technigues, swarm principals, challenges and opportunities in healthcare, blockchain in healthcare today
Swarm learning opens new opportunities for collaboration and innovation in clinical research where all members of the swarm have equal rights. Only algorithms and parameters are shared – with no central authority. Swarm creates many new opportunities in clinical research to develop new therapeutics, epidemiology, genetics research and more. This session will unlock swarm principals, challenges and opportunities in clinical R&D driving wider adoption of its application(s) in the health domain.
Key learnings will include:
- Understanding the differences between federated machine vs swarm learning
- The technical, policy and application barriers when it relates to transferring significant amounts of data
- The steps and frameworks needed to drive wider understanding and adoption of the technology in clinical R&D
- The pharma perspective: where does Swarm AI offer new solutions yet to be introduced to the drug development process
How to Cite
Copyright (c) 2022 Maria Palombini, Director, Healthcare and Life Sciences Practice, IEEE SA , Prof. Dr. Joachim L. Schultze, Director Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE); Director, Genomics & Immunoregulation, LIMES-Institute, University of Bonn Germany, Krishnaprasad Shastry, Director, Distinguished Technologist, Hewlett Packard Enterprise (HPE), Vikram Shetty, Medical Director, Singapore and Asia Area Lung Cancer Lead, AstraZeneca
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