人工智能融合临床与多组学数据在卒中防治及医药研发中的应用与挑战Applications and Challenges of Integrating Artificial Intelligence with Clinical and Multi-omics Data in Stroke Prevention, Treatment, and Pharmaceutical Research and Development
卒中是全球致死致残的首要病因。基于人工智能（artificial intelligence，AI）融合临床与多组学数据的研究范式，为卒中精准防治提供了新方案。AI技术通过整合分析临床与多组学数据，能够提升卒中高危人群识别能力，优化早期诊断与风险评估，实现卒中亚型的精准分型，同时可筛选潜在药物靶点，构建预后预测模型。然而，卒中多组学资源相对匮乏、多模态数据融合困难，以及算法可解释性不足等仍是临床转化的主要瓶颈。本文对AI融合临床与多组学数据在卒中防治及医药研发中的应用与挑战等研究进展进行综述。Abstract: Stroke is the leading global cause of dea...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Chinese Journal of Stroke
2025-06-01
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| Series: | Zhongguo cuzhong zazhi |
| Subjects: | |
| Online Access: | https://www.chinastroke.org.cn/CN/10.3969/j.issn.1673-5765.2025.06.006 |
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| Summary: | 卒中是全球致死致残的首要病因。基于人工智能（artificial intelligence，AI）融合临床与多组学数据的研究范式，为卒中精准防治提供了新方案。AI技术通过整合分析临床与多组学数据，能够提升卒中高危人群识别能力，优化早期诊断与风险评估，实现卒中亚型的精准分型，同时可筛选潜在药物靶点，构建预后预测模型。然而，卒中多组学资源相对匮乏、多模态数据融合困难，以及算法可解释性不足等仍是临床转化的主要瓶颈。本文对AI融合临床与多组学数据在卒中防治及医药研发中的应用与挑战等研究进展进行综述。Abstract: Stroke is the leading global cause of death and disability. The research paradigm that integrates artificial intelligence (AI) with clinical and multi-omics data provides novel solutions for the precision prevention and treatment of stroke. By integrating and analyzing clinical and multi-omics data, AI technology enhances the identification of high-risk populations, optimizes early diagnosis and risk assessment, enables precise subtyping of stroke, facilitates the screening of potential drug targets, and constructs prognostic prediction models. However, critical challenges, such as insufficient multi-omics resources, difficulties in multi modal data integration, and limited interpretability of algorithms, remain major bottlenecks in clinical translation. This article reviews the advances and challenges in AI-driven integration of clinical and multi-omics data in stroke prevention and treatment as well as pharmaceutical research and development. |
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| ISSN: | 1673-5765 |