Anna Bakidou

Doctoral Student at Biomedical Signals and Systems

Anna Bakidou is a PhD student in the Biomedical Signals and Systems research group. Her research is a part of the project "Artificial intelligence (AI) as decision support – for equal care", a collaboration between Chalmers University of Technology, the University of Borås and Østfold University College.
The aim of the research is to develop a decision support system based on AI for trauma patients that recommends appropriate transport destinations for the prehospital emergency care services. Implementation of AI models in triage of trauma patients introduces a mathematical basis that supports the ambulance personnel when determining the transport destination. Furthermore, the use of mathematical models can potentially decrease the mortality among trauma patients by suggesting a destination that is further away than the closest hospital, but that has more appropriate resources.

Source: chalmers.se
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Showing 6 publications

2024

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

Hoor Jalo, Eunji Lee, Mattias Seth et al
Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2
Paper in proceeding
2024

Reviewing Challenges in Specifying Interoperability Requirement in Procurement of Health Information Systems

Mattias Seth, Hoor Jalo, Eunji Lee et al
Studies in Health Technology and Informatics. Vol. 310, p. 8-12
Journal article
2024

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

Hoor Jalo, Eunji Lee, Mattias Seth et al
Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies . Vol. 2, p. 458-465
Paper in proceeding
2023

Early identification and characterisation of stroke to support prehospital decision-making using artificial intelligence: a scoping review protocol

Hoor Jalo, Mattias Seth, Minna Pikkarainen et al
BMJ Open. Vol. 13 (5), p. e069660-
Journal article
2023

Design for integrating explainable AI for dynamic risk prediction in prehospital IT systems

David Wallstén, Gregory Axton, Eunji Lee et al
Artificial Intelligence, Social Computing and Wearable Technologies. Vol. 113, p. 268-278
Paper in proceeding
2023

On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry

Anna Bakidou, Eva Corina Caragounis, M. A. Hagiwara et al
BMC Medical Informatics and Decision Making. Vol. 23 (1)
Journal article

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