A Comparison of Rule-Based and Machine Learning Methods for Medical Information Extraction

机译：基于规则和机器学习方法的医学信息提取方法的比较

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This year's MedNLP (Morita and Kano, et al, 2013) has two tasks: de-identification and complaint and diagnosis. We tested both machine learning based methods and an ad-hoc rule-based method for the two tasks. For the de-identification task, the rule-based method achieved slightly higher results, while for the complaint and diagnosis task, the machine learning based method had much higher recalls and overall scores. These results suggest that these methods should be applied selectively depending on the nature of the information to be extracted, that is to say, whether it can be easily patternized or not.

机译：今年的MedNLP（Morita和Kano等人，2013）具有两项任务：去识别，投诉和诊断。我们针对这两个任务测试了基于机器学习的方法和基于即席规则的方法。对于去识别任务，基于规则的方法取得了略高的结果，而对于投诉和诊断任务，基于机器学习的方法具有更高的召回率和总体得分。这些结果表明，应根据要提取的信息的性质（即，是否可以轻松地对其进行图案化）选择性地应用这些方法。

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《First Workshop on natural language processing for medical and healthcare fields 2013》|2013年|38-42|共5页
会议地点 Nagoya(JP)
作者
Osamu Imaichi; Toshihiko Yanase; Yoshiki Niwa;
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Hitachi, Ltd., Central Research Laboratory 1-280, Higashi-Koigakubo Kokubunji-shi, Tokyo 185-8601;

Hitachi, Ltd., Central Research Laboratory 1-280, Higashi-Koigakubo Kokubunji-shi, Tokyo 185-8601;

Hitachi, Ltd., Central Research Laboratory 1-280, Higashi-Koigakubo Kokubunji-shi, Tokyo 185-8601;

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A Comparison of Rule-Based and Machine Learning Methods for Medical Information Extraction

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