论文标题
克拉拉：临床报告自动完成
CLARA: Clinical Report Auto-completion
论文作者
论文摘要
从X射线和脑电图（EEG）等原始记录中产生临床报告是医生的必要和常规任务。但是，编写准确详细的报告通常很耗时。大多数现有方法试图从原始输入中生成整个报告，因为1）生成的报告通常包含需要手动审查和校正的错误，2）当医生想将其他信息写入报告中时，它并不能节省时间； 3）未根据个人医生的偏好来定制生成的报告。我们提出{\ it cl} inic {\ it a} l {\ it r} eport {\ it a} uto-completion（clara），一种交互式方法，一种互动方法，该方法根据医生的锚词和部分完成句子，根据句子的方式以句子方式生成句子报告。克拉拉（Clara）从现有报告中搜索最相关的句子作为当前报告的模板。通过与输入特征表示形式结合以创建最终报告，可以顺序修改检索到的句子。在我们的实验评估中，Clara在X射线报告中获得了0.393苹果酒和0.248 BLEU-4和0.482 CIDER和0.491 BLEU-4，用于句子级生成的EEG报告，比最佳基线提高了35％。同样，通过我们的定性评估，克拉拉（Clara）在用户研究中得到了医生的认可水平明显较高的报告（Clara 5中的3.74，而基线为2.52中的2.52个）。
Generating clinical reports from raw recordings such as X-rays and electroencephalogram (EEG) is an essential and routine task for doctors. However, it is often time-consuming to write accurate and detailed reports. Most existing methods try to generate the whole reports from the raw input with limited success because 1) generated reports often contain errors that need manual review and correction, 2) it does not save time when doctors want to write additional information into the report, and 3) the generated reports are not customized based on individual doctors' preference. We propose {\it CL}inic{\it A}l {\it R}eport {\it A}uto-completion (CLARA), an interactive method that generates reports in a sentence by sentence fashion based on doctors' anchor words and partially completed sentences. CLARA searches for most relevant sentences from existing reports as the template for the current report. The retrieved sentences are sequentially modified by combining with the input feature representations to create the final report. In our experimental evaluation, CLARA achieved 0.393 CIDEr and 0.248 BLEU-4 on X-ray reports and 0.482 CIDEr and 0.491 BLEU-4 for EEG reports for sentence-level generation, which is up to 35% improvement over the best baseline. Also via our qualitative evaluation, CLARA is shown to produce reports which have a significantly higher level of approval by doctors in a user study (3.74 out of 5 for CLARA vs 2.52 out of 5 for the baseline).
