[1]凌 天,焦 阳,狄碧云,等.面向机器学习的智慧诊疗语料库构建研究[J].医学信息,2023,36(10):6-10.[doi:10.3969/j.issn.1006-1959.2023.10.002]
　LING Tian,JIAO Yang,DI Bi-yun,et al.Research on the Construction of Intelligent Diagnosis and Treatment Corpus for Machine Learning[J].Journal of Medical Information,2023,36(10):6-10.[doi:10.3969/j.issn.1006-1959.2023.10.002]
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面向机器学习的智慧诊疗语料库构建研究()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年10期
页码:
6-10
栏目:
卫生管理信息学
出版日期:
2023-05-15

文章信息/Info

Title:
Research on the Construction of Intelligent Diagnosis and Treatment Corpus for Machine Learning
文章编号:
1006-1959（2023）10-0006-05
作者:
凌 天; 焦 阳; 狄碧云; 等
（浙江中医药大学图书馆，浙江 杭州 310053）
Author(s):
LING Tian; JIAO Yang; DI Bi-yun; et al.
(Library of Zhejiang Chinese Medical University,Hangzhou 310053,Zhejiang,China)
关键词:
语料库; 诊疗; 机器学习
Keywords:
Corpus; Diagnosis and treatment; Machine learning
分类号:
TN911-34
DOI:
10.3969/j.issn.1006-1959.2023.10.002
文献标志码:
A
摘要:
随着人工智能与大数据新兴理论技术发展，语料库由最初单语发展到双语语料库。语料内容由语言学扩展到文学、事实、政治、医学等建设。机器学习技术兴起降低了语料库获取足够规模语料的难度，并针对当下医疗行业医疗资源与需求不平衡问题提供有效解决方案。本文在动态分析语料库研究综述基础上，将复杂的疾病症状、真实的经临床病历、有效的治疗措施等等汇编成语料，以为社会提供智慧服务为目标，提出一种在面向机器学习的智慧诊疗语料库构建的思路。面向机器学习的智慧诊疗语料库构建过程，并探索可视化信息服务、智能语音病历、辅助治疗决策及风险预警应用场景。
Abstract:
With the development of artificial intelligence and emerging theory and technology of big data, the corpus has developed from the initial monolingual to the bilingual corpus, and the content of the corpus has been expanded from linguistics to the construction of literature, facts, politics, medicine, etc. With the development of machine learning technology, the rise reduces the difficulty of obtaining sufficient scale corpus from the corpus, and provides an effective solution to the current imbalance of medical resources and demand in the medical industry. Based on the review of dynamic analysis corpus research, this paper compiles complex disease symptoms, real clinical medical records, effective treatment measures and so on into idiom materials, aiming at providing intelligent services for the society, and puts forward an idea of constructing intelligent diagnosis and treatment corpus for machine learning; the construction process of intelligent diagnosis and treatment corpus for machine learning, and explore the application scenarios of visual information service, intelligent voice medical records, auxiliary treatment decision-making and risk early warning.

参考文献/References:

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更新日期/Last Update: 1900-01-01