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AI Approaches in Processing and Using Data in Personalized Medicine

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Advances in Databases and Information Systems (ADBIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13389))

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Abstract

Nowadays, more and more people suffer from serious diseases and doctors and patients need sophisticated medical and health support. Accordingly, prominent health stakeholders have recognized the importance of development of such services to make patients’ life easier. Such support requires the collection of patients’ complex data. Holistic patient’s data must be properly aggregated, processed, analyzed, and presented to the doctors/caregivers to recommend adequate treatment and actions to improve patient’s health related parameters. Advanced artificial intelligence techniques offer the opportunity to analyze such big data, consume them, and derive new knowledge to support (personalized) medical decisions. New approaches like those based on advanced machine/deep learning, federated learning, transfer learning, explainable artificial intelligence open new paths for more quality use of health and medical data in future. In this paper, we will present some crucial aspects and examples of application of artificial intelligence approaches in (personalized) medical decisions.

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Acknowledgments

This research was supported by the ASCAPE project. The ASCAPE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875351.

Author information

Authors and Affiliations

  1. Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia

    Mirjana Ivanovic

  2. German Research Center for Artificial Intelligence (DFKI), Bremen, Germany

    Serge Autexier

  3. Netcompany-Intrasoft S.A., Luxembourg, Luxembourg

    Miltiadis Kokkonidis

Authors
  1. Mirjana Ivanovic
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  2. Serge Autexier
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  3. Miltiadis Kokkonidis
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Corresponding author

Correspondence to Mirjana Ivanovic .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Silvia Chiusano

  2. Politecnico di Torino, Turin, Italy

    Tania Cerquitelli

  3. Poznań University of Technology, Poznań, Poland

    Robert Wrembel

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Ivanovic, M., Autexier, S., Kokkonidis, M. (2022). AI Approaches in Processing and Using Data in Personalized Medicine. In: Chiusano, S., Cerquitelli, T., Wrembel, R. (eds) Advances in Databases and Information Systems. ADBIS 2022. Lecture Notes in Computer Science, vol 13389. Springer, Cham. https://doi.org/10.1007/978-3-031-15740-0_2

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  • DOI: https://doi.org/10.1007/978-3-031-15740-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15739-4

  • Online ISBN: 978-3-031-15740-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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