高技术通讯2026，Vol.36Issue(7)：724-730,7.DOI:10.3772/j.issn.1002-0470.2026.07.006
基于数据湖的非结构化医疗数据高效检索方法
Efficient retrieval method for unstructured medical data based on data lake
摘要
Abstract
With the widespread adoption of intelligent medical devices,unstructured medical data has grown explosively.Efficient retrieval and management of such data are essential for data mining,exploratory analysis,and artificial in-telligence applications in the medical domain,thereby assisting clinicians in optimizing treatment decisions.How-ever,existing data retrieval methods primarily focus on the semantic representation of data entities and lack the op-timization of retrieval algorithms,resulting in low efficiency of large-scale data retrieval.High-dimensional indexes and distributed storage platforms are effective approaches to improving retrieval efficiency,but prior research has not achieved their effective integration,resulting in shortcomings in both retrieval performance and storage flexibil-ity.To address the above challenges,this paper proposes EMUD(efficient retrieval method for unstructured medical data based on data lake),an efficient retrieval method for unstructured medical data based on data lake.It levera-ges a novel high-dimensional index combined with distributed computing capabilities to enhance the retrieval effi-ciency of unstructured medical data significantly.Meanwhile,EMUD integrates the flexible data storage character-istics of the data lake to achieve efficient management of unstructured medical data and provide a scalable data sup-port interface for cutting-edge medical applications.The experimental results demonstrate that EMUD outperforms other high-dimensional indexes regarding retrieval accuracy,retrieval efficiency,and index construction time under the condition of using less storage space.关键词
数据湖/非结构化医疗数据/高效检索/高维索引Key words
data lake/unstructured medical data/efficient retrieval/high-dimensional index引用本文复制引用
王凯歌,王炜凡,胡振涛,金勇..基于数据湖的非结构化医疗数据高效检索方法[J].高技术通讯,2026,36(7):724-730,7.基金项目
河南省科技攻关计划(252102211041,262102211085)资助项目. （252102211041,262102211085）
