Intelligence-Based Recommendation System for Critical Stroke Management in Intensive Care Units

Luis García Terriza, José Risco-Martín, José Ayala, Gemma Roselló

2023

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.

Download


Paper Citation


in Harvard Style

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) - Volume 3: BIOINFORMATICS; ISBN 978-989-758-631-6, SciTePress, pages 131-138. DOI: 10.5220/0011621000003414


in Bibtex Style

@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) - Volume 3: BIOINFORMATICS},
year={2023},
pages={131-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011621000003414},
isbn={978-989-758-631-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 3: BIOINFORMATICS
TI - Intelligence-Based Recommendation System for Critical Stroke Management in Intensive Care Units
SN - 978-989-758-631-6
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