Stroke Prehospital Decision Support Systems Based on Artificial Intelligence: Grey Literature Scoping Review

Hoor Jalo, Eunji Lee, Mattias Seth, Anna Bakidou, Anna Bakidou, Minna Pikkarainen, Minna Pikkarainen, Katarina Jood, Katarina Jood, Bengt Sjöqvist, Stefan Candefjord

2024

Abstract

Stroke is a leading cause of mortality and disability worldwide. Therefore, there is a growing interest in prehospital point-of-care stroke clinical decision support systems (CDSSs), which with improved precision can identify stroke and decrease the time to optimal treatment, thereby improving clinical outcomes. Artificial intelligence (AI) may be a route to improve CDSSs for clinical benefit. Deploying AI in the area of prehospital stroke care is still in its infancy. There are several existing systematic and scoping reviews summarizing the progress of AI methods for stroke assessment. None of these reviews include grey literature, which could be a valuable source of information, especially when analysing future research and development directions. This paper aims to use grey literature to investigate stroke assessment CDSSs based on AI. The study adheres to PRISMA guidelines and presents seven records showcasing promising technologies. These records included three clinical trials, two smartphone applications, one master thesis and one PhD dissertation, which identify electroencephalogram (EEG), video analysis and voice and facial recognition as potential data sources for early stroke identification. The integration of these technologies may offer the prospect of faster and more accurate CDSSs in the future.

Paper Citation

in Harvard Style

Jalo H., Lee E., Seth M., Bakidou A., Pikkarainen M., Jood K., Sjöqvist B. and Candefjord S. (2024). Stroke Prehospital Decision Support Systems Based on Artificial Intelligence: Grey Literature Scoping Review. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 458-465. DOI: 10.5220/0012380400003657

in Bibtex Style

@conference{healthinf24,
author={Hoor Jalo and Eunji Lee and Mattias Seth and Anna Bakidou and Minna Pikkarainen and Katarina Jood and Bengt Sjöqvist and Stefan Candefjord},
title={Stroke Prehospital Decision Support Systems Based on Artificial Intelligence: Grey Literature Scoping Review},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={458-465},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012380400003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Stroke Prehospital Decision Support Systems Based on Artificial Intelligence: Grey Literature Scoping Review
SN - 978-989-758-688-0
AU - Jalo H.
AU - Lee E.
AU - Seth M.
AU - Bakidou A.
AU - Pikkarainen M.
AU - Jood K.
AU - Sjöqvist B.
AU - Candefjord S.
PY - 2024
SP - 458
EP - 465
DO - 10.5220/0012380400003657
PB - SciTePress