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Profilbild för Towards streamlining prehospital stroke care through AI-driven decision support systems: The ASAP Stroke project

Towards streamlining prehospital stroke care through AI-driven decision support systems: The ASAP Stroke project

Torsdag 22 maj 2025 10:30 - 11:00 F1

Föreläsare: Hoor Jalo

Spår: Future Health and Care

In the critical phase of prehospital stroke care, early, rapid and accurate assessment of the type of stroke and its severity is crucial for improving treatment decisions and patient outcomes. Ambulance personnel, as the first point of contact, face significant challenges, including limited assessment tools, time constraints and the critical nature of stroke management. Advanced tools and clinical decision support systems (CDSS) could enable precise and timely decision-making in these complex environments.

The Care@Distance research group at Chalmers University of Technology has focused on enhancing prehospital care pathways by exploring how digital technologies can improve outcomes based on the motto of increasing precision in all decisions. The group works towards a zero-error vision in assessment, prioritization and handling and considers cooperation between academia, industry and healthcare as essential for ensuring clinical relevance and usability. The projects are planned based on the general structure Acute Support Assessment and Prioritizing (ASAP), which integrates data fusion, clinical decision support, machine learning, telemedicine and innovative user interfaces to support the development of healthcare applications.

The ASAP Stroke project focuses on leveraging artificial intelligence (AI) based CDSS to assist in the early assessment and triage of stroke patients in prehospital settings. By integrating diverse data sources including registry data, videos, vital signs, etc., the project aims to develop predictive models capable of identifying stroke, distinguishing large vessel occlusion strokes and predicting optimal care pathways. To address ethical and privacy concerns, synthetic data generation is also explored, enabling robust model development without compromising patient confidentiality.

This presentation will highlight the objectives, methodologies and future directions of the ASAP Stroke project. By streamlining the early identification of stroke and optimizing patient triage, this project aims to bridge the gap between prehospital and in-hospital stroke assessment. ASAP Stroke aspires to transform prehospital care into a more efficient, accurate and patient-centered care, thereby reducing time-to-treatment and improving outcomes for stroke patients.


Authors: Hoor Jalo1, Bengt Arne Sjöqvist1, Stefan Candefjord1

1) Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden

Språk

English

Ämne

Teknik

Seminarietyp

Live + på plats

Föreläsningsformat

Presentation

Föreläsningssyfte

Verktyg för implementering

Kunskapsnivå

Introduktion

Målgrupp

Tekniker/IT/Utvecklare
Forskare (även studerande)
Studerande
Vårdpersonal

Nyckelord

Personcentrering
Innovativ/forskning
Test/validering

Föreläsare

Hoor Jalo Föreläsare

Chalmers University of Technology