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Data-to-text summarisation of patient records: Using computer-generated summaries to access patient histories

机译：病历的数据到文本摘要：使用计算机生成的摘要访问病史

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摘要

Objective: We assess the efficacy and utility of automatically generated textual summaries of patients' medical histories at the point of care. Method: Twenty-one clinicians were presented with information about two cancer patients and asked to answer key questions. For each clinician, the information on one of the patients comprised their official hospital records, and for the other patient it comprised summaries that were computer-generated by a natural language generation system from data extracted from the official records. We measured the accuracy of the clinicians' responses to the questions, the time they took to complete them, and recorded their attitude to the computer-generated summaries. Results: Results showed no significant difference in the accuracy of responses to the computer-generated records over the official records, but a significant difference in the time taken to assess the patients' condition from the computer-generated records. Clinicians expressed a positive attitude towards the computer-generated records. Conclusion: AI-based computer-generated textual summaries of patient histories can be as accurate as, and more efficient than, human-produced patient records for clinicians seeking to accurately identify key information about a patients overall history. Practice implications: Computer-generated textual summaries of patient histories can contribute to the management of patients at the point-of-care.
机译：目的：我们评估在护理时自动生成的患者病史文本摘要的功效和效用。方法：向21位临床医生提供了有关两名癌症患者的信息，并要求他们回答关键问题。对于每位临床医生而言，其中一位患者的信息包括他们的正式医院记录，而另一位患者的信息则包括摘要，这些摘要由自然语言生成系统根据从官方记录中提取的数据进行计算机生成。我们测量了临床医生对问题的回答的准确性，完成问题所需的时间，并记录了他们对计算机生成的摘要的态度。结果：结果显示，对计算机生成记录的答复准确性与官方记录相比没有显着差异，但是从计算机生成记录评估患者状况所花费的时间却存在显着差异。临床医生对计算机生成的记录表示积极的态度。结论：基于AI的计算机生成的患者历史记录的文本摘要与人工生成的患者记录一样准确，并且比人工生成的患者记录更有效，以帮助临床医生准确识别有关患者总体历史记录的关键信息。实践意义：计算机生成的患者历史记录文本摘要可有助于在护理点对患者进行管理。

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