This project forked from shibing624/case-analysis
NLP之病历分析：从病历文本之中提取关键信息，便于后续分析处理。
License: Apache License 2.0
NLP之病历分析：从病历文本之中提取关键信息，便于后续分析处理。
要求： 需求简单的概况就是从病历文本之中提取关键信息，命名实体识别，包括分词和词性标注
提取关键信息（关键词数量），命名实体识别（这个有准确度问题的，哪些实体，现在知道包括病症名称、药品名称，其他不晓得了），包括分词和词性标注（主流词性要求+病症名称词性和药品词性区分开来？）
六大类实体
病症名称词性和药品词性要区分的
1.从一端文本之中抽取结构化的数据，比如从一段病历文本之中提取疾病、症状、药品、手术，或者从一端文本之中提取地名、公司名称。 2.识别出这些信息的关系。
要求使用python语言实现，最好使用CRF（条件随机场）实现 。
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