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Most of the clinical narratives are free-text forms. The information extractions from clinical narrative text are more complicated than those from other biomedical texts, such as books, articles, literature abstracts, and so on. In this paper, we review recent published researches on the implication and technology of information extraction from free-text clinical narratives. We mainly introduce the Hidden Markov Model, Support Vector Machine, Ontology and other combined method used indoi:10.12783/ijcsa.2015.0402.01 fatcat:4cch3i72jjbo5hvnbbssvwnnpi