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Federated Learning in Healthcare with Unsupervised and Semi-Supervised Methods

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Flexible Query Answering Systems (FQAS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14113))

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Abstract

The federated paradigm has made possible the development of techniques capable of solving advanced problems in the healthcare field through the protection of data privacy. However, most existing research is centered around supervised methods and real world data tends to be unevenly distributed and scarcely labelled. This paper aims to provide an overview of existing unsupervised and semi-supervised methods implemented in a federated healthcare setting in order to identify state of the art methods and detect current challenges and future lines of research.

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Acknowledgements

We would like to acknowledge support for this work from the Grant PID2021-123960OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe.

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Authors and Affiliations

  1. Department of Computer Science and A.I., Research Centre for Information and Communication Technologies (CITIC -UGR), University of Granada, Granada, Spain

    Juan Paños-Basterra, M. Dolores Ruiz & Maria J. Martin-Bautista

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  1. Juan Paños-Basterra
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  2. M. Dolores Ruiz
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  3. Maria J. Martin-Bautista
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Correspondence to Juan Paños-Basterra .

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Editors and Affiliations

  1. Legind Technologies, Esbjerg V, Denmark

    Henrik Legind Larsen

  2. University of Granada, Granada, Spain

    Maria J. Martin-Bautista

  3. University of Granada, Granada, Spain

    M. Dolores Ruiz

  4. Roskilde University, Roskilde, Denmark

    Troels Andreasen

  5. Consiglio Nazionale delle Ricerche, Milano, Italy

    Gloria Bordogna

  6. Ghent University, Gent, Belgium

    Guy De Tré

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Paños-Basterra, J., Ruiz, M.D., Martin-Bautista, M.J. (2023). Federated Learning in Healthcare with Unsupervised and Semi-Supervised Methods. In: Larsen, H.L., Martin-Bautista, M.J., Ruiz, M.D., Andreasen, T., Bordogna, G., De Tré, G. (eds) Flexible Query Answering Systems. FQAS 2023. Lecture Notes in Computer Science(), vol 14113. Springer, Cham. https://doi.org/10.1007/978-3-031-42935-4_15

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  • DOI: https://doi.org/10.1007/978-3-031-42935-4_15

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