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Authors: Luis García Terriza 1 ; José Risco-Martín 1 ; José Ayala 1 and Gemma Roselló 2

Affiliations: 1 Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain ; 2 Stroke Care Unit, Hospital Universitario de La Princesa, Spain

Keyword(s): Machine Learning, Genetic Algorithms, Health Recommendation System, Death Risk Prediction, Decision Support System.

Abstract: This work presents an integrated recommendation system capable of providing support in healthcare critical environments such as Intensive Care Units or Stroke Care Units using Machine Learning techniques. The system can manage several patients by reading monitoring hemodynamic data in real-time, presenting current death risk probability, and showing recommendations that would reduce such probability and, in some cases, avoid death. This system introduces a novel method to produce recommendations based on genetic models and supervised machine learning. The interface is built upon a web application where clinicians can evaluate recommendations and straightforwardly provide feedback.

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Paper citation in several formats:
García Terriza, L.; Risco-Martín, J.; Ayala, J. and Roselló, G. (2023). Intelligence-Based Recommendation System for Critical Stroke Management in Intensive Care Units. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 131-138. DOI: 10.5220/0011621000003414

@conference{bioinformatics23,
author={Luis {García Terriza}. and José Risco{-}Martín. and José Ayala. and Gemma Roselló.},
title={Intelligence-Based Recommendation System for Critical Stroke Management in Intensive Care Units},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS},
year={2023},
pages={131-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011621000003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS
TI - Intelligence-Based Recommendation System for Critical Stroke Management in Intensive Care Units
SN - 978-989-758-631-6
IS - 2184-4305
AU - García Terriza, L.
AU - Risco-Martín, J.
AU - Ayala, J.
AU - Roselló, G.
PY - 2023
SP - 131
EP - 138
DO - 10.5220/0011621000003414
PB - SciTePress

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