随着医疗行业不断发展,医学数据呈现指数级增长趋势,如何高效处理和利用这些数据成为当前医疗领域面临的一个重要问题.自然语言处理(NLP)技术的不断发展使得医学语言模型的构建成为可能,这为医学数据的挖掘和分析提供了新的途径.文章首先梳理了医学语言模型构建的准备步骤,之后从无监督学习、监督学习和迁移学习等方面叙述了医学语言模型的具体构建方法,并探讨医学语言模型所面临的挑战和未来发展方向.
With the continuous development of the medical industry,medical data shows an exponential growth trend.How to deal with and utilize these data efficiently has become an important issue facing the current medical field.The development of natural language processing(NLP)technology makes it possible to construct medical language model,which provides a new way for medical data mining and analysis.This paper reviews the construction methods of medical language model and its ap-plication in the medical field,including medical text classification,entity recognition,relationship extraction,knowledge map construction and so on.At the same time,this paper discusses the challenges facing the medical language model,including the complexity of language,the particularity of the medical field and data privacy issues.Finally,the future development direction of medical language model is prospected.