AI Approaches in Processing and Using Data in Personalized Medicine
- URL: http://arxiv.org/abs/2208.04698v1
- Date: Tue, 26 Jul 2022 11:11:39 GMT
- Title: AI Approaches in Processing and Using Data in Personalized Medicine
- Authors: Mirjana Ivanovic (1), Serge Autexier (2) and Miltiadis Kokkonidis (3)
((1) University of Novi Sad, Faculty of Sciences, Novi Sad, Serbia, (2)
German Research Center for Artificial Intelligence (DFKI), Bremen Site,
Germany, (3) Netcompany-Intrasoft S.A., Luxembourg, Luxembourg)
- Abstract summary: 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 learning, federated learning, transfer learning, explainable artificial intelligence open new paths for more quality use of health and medical data in future.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In modern dynamic constantly developing society, more and more people suffer
from chronic and serious diseases and doctors and patients need special and
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 huge amount
of patients complex data like clinical, environmental, nutritional, daily
activities, variety of data from smart wearable devices, data from clothing
equipped with sensors etc. Holistic patients data must be properly aggregated,
processed, analyzed, and presented to the doctors and caregivers to recommend
adequate treatment and actions to improve patients health related parameters
and general wellbeing. 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 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
characteristic examples in the area of application of a range of artificial
intelligence approaches in personalized medical decisions.
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