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PervasiveHealth: Pervasive Computing Technologies for Healthcare20 May 2019, Pages 399-40213th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2019; Trento; Italy; 20 May 2019 through 23 May 2019; Code 148577

Adding AI to the decision support system used in patient health assessment(Conference Paper)

  • Vidaković, M.,
  • Ćosić, S.,
  • Ćosić, O.,
  • Kaštelan, I.,
  • Velikić, G.
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  • aDepartment of Computing and Control Engineering, University of Novi Sad, Faculty of Technical Sciences Novi, Sad, Serbia
  • bRT-RK Institute for Computer Based Systems Novi, Sad, Serbia

Abstract

This paper describes one solution for embedding an Artificial Intelligence (AI) framework into the Decision Support System (DSS) used for a patient health assessment and life improvement. The DSS processes sensor-acquired health parameters and various health-related data in order to give an assessment of the patient health condition as well as to try to predict the possibility of the patient having another major health decline, such as stroke. The initial DSS version processes data using the statistical methods and proprietary algorithms which did not employ AI techniques. Rapid emergence of the AI frameworks, and evidence of clearly noticeable better results for systems based on AI, motivated us to integrate AI into the DSS. In this paper we present integration of TensorFlow framework in the DSS. © 2019 Association for Computing Machinery.

Author keywords

Artificial intelligenceDecision support systemTensorFlow

Indexed keywords

Engineering controlled terms:Decision support systemsHealth careUbiquitous computing
Engineering uncontrolled termsAI techniquesDecision support system (dss)DSS processHealth parametersLife improvementPatient healthTensorFlow
Engineering main heading:Artificial intelligence

Funding details

Funding sponsor Funding number Acronym
Horizon 2020 Framework Programme
See opportunities by H2020		H2020
Horizon 2020689947

  • 1

    This work has been funded by the European Union’s Horizon 2020 research and innovation project STARR under grant agreement No. 689947.

  • ISSN: 21531633
  • ISBN: 978-145036126-2
  • Source Type: Conference Proceeding
  • Original language: English
  • DOI: 10.1145/3329189.3329246
  • Document Type: Conference Paper
  • Sponsors: The European Alliance for Innovation (EAI)
  • Publisher: ICST


© Copyright 2022 Elsevier B.V., All rights reserved.

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(2021) International Series in Operations Research and Management Science
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