Imaging-based machine learning to evaluate the severity of ischemic stroke in the middle cerebral artery territory
Abstract Objectives This study aims to develop an imaging-based machine learning model for evaluating the severity of ischemic stroke in the middle cerebral artery (MCA) territory. Methods This retrospective study included 173 patients diagnosed with acute ischemic stroke (AIS) in the MCA territory...
Saved in:
| Main Authors: | Gang Xie, Jin Gao, Jian Liu, Xuwei Zhou, Zhengkai Zhao, Wuli Tang, Yue Zhang, Lingfeng Zhang, Kang Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
|
| Series: | BMC Medical Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12880-025-01745-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Metabolic and Rheological Disorders in Acute Period of Ischemic Stroke
by: I. M. Ustyantseva, et al.
Published: (2007-12-01) -
Impact of hemoglobin levels on acute ischemic stroke severity
by: Shaima Abuhulayqah, et al.
Published: (2025-04-01) -
Investigating the impact of glycated hemoglobin levels on stroke severity in patients with acute ischemic stroke
by: Naif M. Alhawiti, et al.
Published: (2025-04-01) -
Linking Immunological Parameters and Recovery of Patient’s Motor and Cognitive Functions In The Acute Period of Ischemic Stroke
by: A. M. Tynterova, et al.
Published: (2024-02-01) -
Association of phenotypic age and accelerated aging with severity and disability in patients with acute ischemic stroke
by: Yongkang Liu, et al.
Published: (2024-12-01)