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A Field Theoretical Approach to Medical Natural Language Processing

机译:医学自然语言处理的场论方法

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摘要

A parser for medical free text reports has been developed that is based on a chemistry/physics inspired “field theory” for word–word sentence-level dependencies. The transition from the linguistic world to the world of interacting particles with potential energies is guided by a psycholinguistics thought experiment related to the amount of “work” required to bring a reference word into an anchored configuration of words. Calibration experiments involving four and five grams were conducted. Data from these experiments were used as a knowledge source for estimating field conditions for words in sentences sampled from a corpus of medical reports. The result of the parser is a dependency tree that represents the global minimum energy state of the system of words for a given sentence. The system was trained and tested on a corpus of radiology reports. Preliminary performance, as quantified by link recall and precision statistics, is 84.9% and 89.9%, respectively.
机译:已经开发了一种用于医学自由文本报告的解析器,该解析器基于化学/物理学启发的“场论”,用于单词-单词句子级别的依存关系。从语言世界到具有潜在能量的相互作用粒子世界的过渡,是通过心理语言学思想实验指导的,该实验涉及将参考词带入单词的锚定配置所需的“工作”量。进行了涉及四克和五克的校准实验。这些实验的数据被用作知识来源,用于估计从医疗报告语料库中抽取的句子中单词的现场条件。解析器的结果是一个依赖关系树,它表示给定句子的单词系统的全局最小能量状态。该系统在放射学报告语料库中经过培训和测试。通过链接召回和精确度统计量化的初步性能分别为84.9%和89.9%。

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