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AI Approaches in Processing and Using Data in Personalized Medicine

Mirjana Ivanovic; Serge Autexier; Miltiadis Kokkonidis
In: Silvia Chiusano; Tania Cerquitelli; Robert Wrembel (Hrsg.). Advances in Databases and Information Systems. European Conference on Advances in Databases and Information Systems (ADBIS-2022), September 5-8, Turin, Italy, Pages 11-24, LNCS, Vol. 13389, ISBN 978-3-031-15740-0, Springer International Publishing, 8/2022.


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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