Transformer-Based Abstract Generation of Medical Case Reports

Anusha Verma Chandraju, Lydia J. Gnanasigamani
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Abstract

A medical case report gives medical researchers and healthcare providers a thorough account of the symptoms, treatment, and diagnosis of a specific patient. This clinical data is essential because they aid in diagnosing novel or uncommon illnesses, analyzing specific medical occurrences, and enhancing knowledge of current medical education. The summary of the medical case report is needed so that one can decide on further reading as going through the entire contents of a medical case report istime-consuming. In this paper, we present a deep learning methodology for the generation of the automatic summaries of the medical case reports. The final proposed fine-tuned summarizer on the test data set generated a mean precision of 0.4481 and Rouge-1 Score of 0.2803.
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基于变压器的医疗病例报告摘要生成
医学病例报告为医学研究人员和医疗保健提供者提供了对特定患者的症状、治疗和诊断的全面描述。这些临床数据是必不可少的,因为它们有助于诊断新的或不常见的疾病,分析特定的医疗事件,并提高当前医学教育的知识。医学病例报告的摘要是必要的,以便决定是否进一步阅读,因为浏览整个医学病例报告的内容是费时的。在本文中,我们提出了一种用于医学病例报告自动摘要生成的深度学习方法。最终在测试数据集上提出的微调汇总器生成的平均精度为0.4481,Rouge-1 Score为0.2803。
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