Machine learning-based radiomic analysis of T2-FLAIR white matter hyperintensity predicts hemorrhagic transformation after endovascular thrombectomy for acute ischemic stroke.
Overview & Synopsis
Open access biomedical research article published in BMC Med Imaging.
Indexed from repository: PubMed Central
(
pmc.ncbi.nlm.nih.gov)
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Document Information
| Document Title | Machine learning-based radiomic analysis of T2-FLAIR white matter hyperintensity predicts hemorrhagic transformation after endovascular thrombectomy for acute ischemic stroke. |
|---|---|
| Author / Organization | Wu Q, Shi Y, Zhang Z, Zhang J, Wu J, Yang Z, He Y, Su J, Wang X, Huang C, Zhu X |
| Subject & Discipline | BMC Med Imaging |
| Categories | Medicine & Health |
| Publication Year | 2026 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
PubMed Central
(pmc.ncbi.nlm.nih.gov)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-137477 |
| Original Source Link | Visit Source Page on pmc.ncbi.nlm.nih.gov » |