Abstract
The early diagnosis and personalized treatment of acute ischemic stroke (AIS) are unmet clinical challenges. The recent development of neuroimaging technologies provides more in-depth information on brain circulation that can be used for the clinical management of AIS. Artificial intelligence (AI), including machine learning and deep learning models, enables the data-driven early diagnosis of AIS. Radiomic analysis can extract AIS-associated deep features from neuroimaging data. The fusion of multimodal data further enhances the diagnostic power of AI models. Meanwhile, many AI models are limited by the sample size with a lack of validation on big data. This chapter provides an updated review on recent works and summarizes the advantages and challenges of AI models based on neuroimaging data in the diagnosis of treatment of AIS, offering a reference for clinicians, data scientists, and biomedical engineers.
| Original language | English |
|---|---|
| Title of host publication | Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases |
| Subtitle of host publication | Towards Data-Driven Smart Healthcare |
| Editors | Haipeng Liu, Gary Tse |
| Publisher | CRC Press, Taylor & Francis Group |
| Chapter | 13 |
| Pages | 232-248 |
| Number of pages | 17 |
| Edition | 1 |
| ISBN (Electronic) | 9781003481621 |
| ISBN (Print) | 9781032771694 |
| DOIs | |
| Publication status | Published - 23 Jun 2025 |
Bibliographical note
Publisher Copyright:© 2025 selection and editorial matter, Haipeng Liu and Gary Tse; individual chapters, the contributors.