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 |
|---|---|
| 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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