Imaging-based machine learning to evaluate the severity of ischemic stroke in the middle cerebral artery territory.
- Published in:
- BMC Medical Imaging, 2025, v. 25, n. 1, p. 1, doi. 10.1186/s12880-025-01745-7
- By:
- Publication type:
- Article
Works by Tang, Wuli
Results: 7
1
2
A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study.
- Published in:
- Frontiers in Neuroscience, 2024, p. 1, doi. 10.3389/fnins.2024.1443486
- By:
- Publication type:
- Article
3
Radiomics nomogram based on dual-energy CT-derived iodine maps: evaluation of mucosal healing in patients with Crohn's disease.
- Published in:
- Abdominal Radiology, 2025, v. 50, n. 4, p. 1524, doi. 10.1007/s00261-024-04598-w
- By:
- Publication type:
- Article
4
Constructing machine learning models based on non-contrast CT radiomics to predict hemorrhagic transformation after stoke: a two-center study.
- Published in:
- Frontiers in Neurology, 2024, p. 1, doi. 10.3389/fneur.2024.1413795
- By:
- Publication type:
- Article
5
Establishing a machine learning model based on dual-energy CT enterography to evaluate Crohn's disease activity.
- Published in:
- Insights into Imaging, 2024, v. 15, n. 1, p. 1, doi. 10.1186/s13244-024-01703-x
- By:
- Publication type:
- Article
6
Radiomics-based infarct features on CT predict hemorrhagic transformation in patients with acute ischemic stroke.
- Published in:
- Frontiers in Neuroscience, 2022, v. 16, p. 1, doi. 10.3389/fnins.2022.1002717
- By:
- Publication type:
- Article
7
Imaging-based assessment of body composition in patients with Crohn's disease: a systematic review.
- Published in:
- International Journal of Colorectal Disease, 2023, v. 38, n. 1, p. 1, doi. 10.1007/s00384-023-04413-w
- By:
- Publication type:
- Article