YTEX和MetaMap用于临床概念识别的评价
Evaluation of YTEX and MetaMap for clinical concept recognition
摘要：
我们使用MetaMap和YTEX作为两个独立系统的验证基础，以参与2013年ShARe/CLEF eHealth任务1[9]，即临床概念的识别。没有直接对这些系统进行修改，但使用停止概念，停止概念文本和UMLS语义类型过滤输出概念。还使用一小部分规则来调整概念边界，以提高严格任务的精度。总体而言，MetaMap在严格的任务上比YTEX具有更好的性能，主要是由于精度提高了20%。在轻松的任务中，YTEX在精确率和召回率方面都有更好的表现，在测试数据上的总体F分数比MetaMap高4.6%。我们的研究结果还表明，在UMLS CUI映射中，YTEX的准确性提高了1.3%。
英文摘要：
We used MetaMap and YTEX as a basis for the construc- tion of two separate systems to participate in the 2013 ShARe/CLEF eHealth Task 1[9], the recognition of clinical concepts. No modifications were directly made to these systems, but output concepts were filtered using stop concepts, stop concept text and UMLS semantic type. Con- cept boundaries were also adjusted using a small collection of rules to increase precision on the strict task. Overall MetaMap had better per- formance than YTEX on the strict task, primarily due to a 20% perfor- mance improvement in precision. In the relaxed task YTEX had better performance in both precision and recall giving it an overall F-Score 4.6% higher than MetaMap on the test data. Our results also indicated a 1.3% higher accuracy for YTEX in UMLS CUI mapping.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
