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      To share or not to share? Privacy-preserving AI in medicine

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      conference-abstract
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      RExPO24 Conference
      REPO4EU
      RExPO24
      3-5 July 2024
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            Abstract

            European Health Data Spaces, national digital health records archives and similar initiatives aim to provide a mixture of legal and technical frameworks to make privacy-sensitive medical data available for data mining. The ultimate goal is to access the yet behind legal barriers hidden healthcare data treasure in order to train prognostic models for personalized medicine - from disease management to individualized drug repurposing prediction. The biggest roadblock is the GDPR. In the talk, we will discuss federated learning technology that - coupled to other privacy-enhancing technologies - allows for a secure multi-center data mining collaboration. Specifically, we will demonstrate that it does provide as accurate results as centralized solutions. We will discuss concrete applications for multi-centric genome-wide association studies, for meta-genomics, transcriptomics and proteomics analysis including batch effect correction, and for survival time analysis. One application involved >1,000 hospitals in North America, another one involves >100,000 European screening participants. Finally, we discuss the limitations and future prospects of federated learning in biomedicine and healthcare data mining.

            Content

            Author and article information

            Conference
            RExPO24 Conference
            REPO4EU
            18 April 2024
            Affiliations
            [1 ] Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany ( https://ror.org/00g30e956)
            Author notes
            Author information
            https://orcid.org/0000-0002-0282-0462
            Article
            10.58647/REXPO.24000035.v1
            467bdd3b-f4ed-48f1-b12f-921463ca0119

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            RExPO24
            3
            Munich, Germany
            3-5 July 2024
            History
            : 18 April 2024
            Product

            REPO4EU

            Categories

            The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
            Artificial intelligence

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