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Automated misspelling detection and correction in clinical free-text records

机译:临床自由文本记录中的自动拼写错误检测和纠正

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摘要

Correct record is important in all fields especially in the medical field. For correct medication, safety of patient and correct documentation accurate medical records are important. There is possibility that medical record can contain some misspelled words that can lead towards the wrong interpretation and wrong treatment of patients. So, it is necessary that the medical record must be correct for proper treatment and care of patients. Part of speech tagging is à mechanism that reads the text in documents and separates the different part of speech. Regular expression is a mechanism that is used to match the specific pattern of words in documents. A Methodology/spellchecker is proposed for automated misspelling detection and correction in medical free-text records for correction of misspelled terms. Proposed methodology is based on part of speech tagging and regular expression and is applied on all types of medical documents such as allergy entries, free-text medication order and clinical notes. Dictionary lookup is used for detection of misspelled words. Suffix and prefix based suggestion list is used for misspelled correction. Incorrect spellings from different medical documents are detected and corrected. A significant percentage of misspelling detection and correction is achieved.
机译:正确的记录在所有领域都很重要,尤其是在医疗领域。对于正确的用药,患者的安全和正确的记录,准确的医疗记录很重要。病历中可能包含一些拼写错误的单词,可能导致错误的解释和错误的患者治疗。因此,为了正确治疗和护理患者,病历必须正确。语音标记的一部分是à机制,可读取文档中的文本并将语音的不同部分分开。正则表达式是一种用于匹配文档中特定单词模式的机制。提出了一种方法/拼写检查器,用于医学自由文本记录中的自动拼写错误检测和纠正,以纠正拼写错误的术语。拟议的方法基于语音标记和正则表达式,并适用于所有类型的医学文档,例如过敏条目,自由文本药物处方和临床记录。字典查找用于检测拼写错误的单词。基于后缀和前缀的建议列表用于拼写错误的更正。检测并纠正了来自不同医学文档的不正确拼写。实现了很大百分比的拼写错误检测和纠正。

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