Prediction of Stroke Using Brain Computed Tomography (CT) Images

Seydou Nourou Sylla; Sangoulé Ndao; Adrien Bass

Innovations and Interdisciplinary Solutions for Underserved Areas. 8th International Conference, InterSol 2025, Ouagadougou, Burkina Faso, July 3–4, 2025, Proceedings

Research Article

Prediction of Stroke Using Brain Computed Tomography (CT) Images

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-032-15154-4_3,
    author={Seydou Nourou Sylla and Sangoul\^{e} Ndao and Adrien Bass},
    title={Prediction of Stroke Using Brain Computed Tomography (CT) Images},
    proceedings={Innovations and Interdisciplinary Solutions for Underserved Areas. 8th International Conference, InterSol 2025, Ouagadougou, Burkina Faso, July 3--4, 2025, Proceedings},
    proceedings_a={INTERSOL},
    year={2026},
    month={11},
    keywords={Stroke CT imaging Deep learning Medical AI Classification},
    doi={10.1007/978-3-032-15154-4_3}
}

Seydou Nourou Sylla
Sangoulé Ndao
Adrien Bass
Year: 2026
Prediction of Stroke Using Brain Computed Tomography (CT) Images
INTERSOL
Springer
DOI: 10.1007/978-3-032-15154-4_3

Seydou Nourou Sylla¹^,*, Sangoulé Ndao¹, Adrien Bass¹

1: University Alioune Diop

*Contact email: seydounourou.sylla@uadb.edu.sn

Abstract

This paper presents an artificial intelligence (AI) model designed to predict strokes using computed tomography (CT) brain images. Stroke is one of the leading causes of mortality and disability in Senegal, where access to advanced diagnostic technologies is limited. The proposed AI system aims to assist radiologists by providing rapid, accurate stroke predictions and is integrated into a mobile application to support diagnosis in remote areas.

Keywords: Stroke, CT imaging, Deep learning, Medical AI, Classification

Published: 2026-11-02
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-032-15154-4_3

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Prediction of Stroke Using Brain Computed Tomography (CT) Images

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