StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images
Article
Article Title | StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images |
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ERA Journal ID | 44807 |
Article Category | Article |
Authors | Ekingen, Evren, Yildirim, Ferhat, Bayar, Ozgur, Akbal, Erhan, Sercek, Ilknur, Hafeez-Baig, Abdul, Dogan, Sengul and Tuncer, Turker |
Journal Title | BMC Medical Imaging |
Journal Citation | 25 (1) |
Article Number | 205 |
Number of Pages | 18 |
Year | 2025 |
Publisher | BioMed Central Ltd. |
Place of Publication | United Kingdom |
ISSN | 1471-2342 |
Digital Object Identifier (DOI) | https://doi.org/10.1186/s12880-025-01721-1 |
Web Address (URL) | https://bmcmedimaging.biomedcentral.com/articles/10.1186/s12880-025-01721-1 |
Abstract | Background and Objective Materials and Methods Results Conclusion |
Keywords | Deep feature engineering; Stroke detection; Patch-based feature extraction |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 4605. Data management and data science |
Byline Affiliations | Etlik City Hospital, Turkey |
Finike City Hospital, Turkey | |
Mamak State Hospital, Turkey | |
Firat University, Turkey | |
School of Business |
https://research.usq.edu.au/item/zy80z/strokenext-an-automated-stroke-classification-model-using-computed-tomography-and-magnetic-resonance-images
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