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DEEP-LEARNING BASED CERTAINTY QUALIFICATION IN DIAGNOSTIC REPORTS

机译:基于深度学习的诊断报告的确定性资格

摘要

A method for assessing diagnostic certainty in diagnostic reporting natural language, the method comprising receiving a natural language impression portion of a diagnostic report submitted for certainty evaluation, the impression portion having one or more sentences of natural language, accessing a pre-trained and fine-tuned language model, applying the one or more sentences to the trained language model for evaluation of the one or more sentences as a whole, receiving an assessment of certainty for the respective one or more sentences, based on the evaluation, communicating the assessment of certainty to a user before accepting the impression portion, and accepting submission of the impression portion only after the impression portion satisfies certainty criteria, or if the certainty criteria is not required obtaining validation from the user.
机译:一种评估诊断报告自然语言诊断确定的方法,该方法包括接收提交的诊断报告的自然语言印象部分,提交了确定性评估,具有自然语言的一个或多个句子的印象部分,访问预训练和精细 - 调谐语言模型,将一个或多个句子应用于培训的语言模型,以评估一个或多个句子的整体,基于评估,接受对各自的一个或多个句子的确定性评估,传达确定性评估 在接受印象部分之前,并且仅在印模部分满足确定性标准之后接受印模部分的提交,或者如果不需要从用户获取验证,则仅接受印模部分的提交。

著录项

  • 公开/公告号US2021407679A1

    专利类型

  • 公开/公告日2021-12-30

    原文格式PDF

  • 申请/专利权人 UNIVERSITY OF MASSACHUSETTS;

    申请/专利号US202117358481

  • 发明设计人 FEIFAN LIU;MAX P. ROSEN;

    申请日2021-06-25

  • 分类号G16H50/20;G06N3/08;G16H15;G06K9/62;G06F40/20;

  • 国家 US

  • 入库时间 2022-08-24 23:07:16

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