A machine learning-based predictive model for predicting early neurological deterioration in lenticulostriate atheromatous disease-related infarction
The novel nomogram incorporating systolic pressure, stroke history, conglomerated beads sign, parent artery stenosis, and MCA shape provides a practical tool for assessing the risk of early neurological deterioration in BAD affecting the LSA territory. This model enhances clinical decision-making and personalized treatment strategies.
Authors
- Chen Lou (ORCID: https://orcid.org/0000-0002-5506-5835)
- Hongfei Li (ORCID: https://orcid.org/0000-0001-8312-2721)
- Xiaolan Wu
- Yuan Fang (ORCID: https://orcid.org/0009-0000-6551-0245)
- Dongjuan Xu (ORCID: https://orcid.org/0000-0002-0832-7417)
- Zhuangzhuang Jiang (ORCID: https://orcid.org/0009-0002-5210-543X)
Institutions
- Wenzhou Medical University (CN)
- Dongyang People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2024-12-11
- DOI
- https://doi.org/10.3389/fnins.2024.1496810
- Citations
- 2
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 0.77