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Using Text Prediction for Facilitating Input and Improving Readability of Clinical Text

机译:使用文本预测促进输入和提高临床文本可读性

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Text prediction has the potential for facilitating and speeding up the documentation work within health care, making it possible for health personnel to allocate less time to documentation and more time to patient care. It also offers a way to produce clinical text with fewer misspellings and abbreviations, increasing readability. We have explored how text prediction can be used for input of clinical text, and how the specific challenges of text prediction in this domain can be addressed. A text prediction prototype was constructed using data from a medical journal and from medical terminologies. This prototype achieved keystroke savings of 26% when evaluated on texts mimicking authentic clinical text. The results are encouraging, indicating that there are feasible methods for text prediction in the clinical domain.
机译:文本预测具有促进和加速卫生保健内部的文档工作的可能性,使得卫生人员可以将更少的时间分配给文档和更多时间来患者护理。它还提供了一种方法来生产具有较少的拼写错误和缩写,增加可读性。我们探索了如何用于输入临床文本的文本预测,以及如何解决该域中文本预测的特定挑战。使用来自医学期刊和医学术语的数据构建文本预测原型。当在模仿正宗临床文本的文本评估时,该原型截止了26%的击键节省。结果令人鼓舞,表明临床结构域中存在可行的文本预测方法。

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