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Chapter 4: Recent Advances in federated learning for digital healthcare systems

Title: Chapter 4: Recent Advances in federated learning for digital healthcare systems
Authors: Mohnani, Pooja; Thümmler, Christoph; Avila Castillo, Angelica; Tolba, Rasha; Bassi, Alessandro; Simon, Antoine; Gavras, Anastasius; Toscano, Orazio; Haigron, Pascal
Publisher Information: Zenodo
Publication Year: 2024
Collection: Zenodo
Description: This chapter covers the need & importance of federated learning in digital healthcare system. Federated learning in digital healthcare systems evolves around trust and without leaking of private data, thereby creating sustainability and resilience in these dynamic data ecosystems. It opens-up opportunities for novel research and business domains that can be looked at, as a prominent way to improve patient care globally. Federated learning can innovate the treatment cycle in more than one way, for example, to help finding similar patients, to accelerate drug discovery, or to decrease cost and time-to-market for pharma companies. The chapter covers how federated systems are perceived and what are the important considerations towards their development. The approach helps understanding the need for privacy preservation in a scalable and reliable way. Cutting-edge technologies and recent innovations are employed to oversee and disseminate patient information, aiding the implementation of novel patient-centric care models and services. These advancements have the potential to expedite the digital transformation of both society and the economy.
Document Type: book part
Language: English
Relation: https://zenodo.org/communities/paroma-med/; https://zenodo.org/communities/eu/; https://zenodo.org/records/12666191; oai:zenodo.org:12666191; https://doi.org/10.5281/zenodo.12666191
DOI: 10.5281/zenodo.12666191
Availability: https://doi.org/10.5281/zenodo.12666191; https://zenodo.org/records/12666191
Rights: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number: edsbas.193636F4
Database: BASE