论文标题
听力学报告的听力图数字化工具
Audiogram Digitization Tool for Audiological Reports
论文作者
论文摘要
许多私人保险公司和公共保险公司对听力损失可以直接归因于工作场所中噪音过度暴露的工人进行了补偿。索赔评估过程通常很漫长，需要从人类审判者那里进行大量努力，这些裁决者必须解释经常通过传真或同等数字发送的手录制的听力图。在这项工作中，我们提出了与安大略省工作场所安全保险委员会合作开发的解决方案，以简化裁决过程。特别是，我们提出了第一个能够自动从扫描或传真听力学报告中提取听力阈值的听力图数字化算法作为概念证明。该算法将大多数阈值提取在5 dB的精度之内，从而可以大大减少以半监督的方式将听力图转换为数字格式所需的时间，并且是迈向自动化过程的第一步。 GITHUB（https://github.com/greencubic/audiogramDigitization）公开获得了数字化算法的源代码和我们NIHL注释门户的基于桌面的实现。
A number of private and public insurers compensate workers whose hearing loss can be directly attributed to excessive exposure to noise in the workplace. The claim assessment process is typically lengthy and requires significant effort from human adjudicators who must interpret hand-recorded audiograms, often sent via fax or equivalent. In this work, we present a solution developed in partnership with the Workplace Safety Insurance Board of Ontario to streamline the adjudication process. In particular, we present the first audiogram digitization algorithm capable of automatically extracting the hearing thresholds from a scanned or faxed audiology report as a proof-of-concept. The algorithm extracts most thresholds within 5 dB accuracy, allowing to substantially lessen the time required to convert an audiogram into digital format in a semi-supervised fashion, and is a first step towards the automation of the adjudication process. The source code for the digitization algorithm and a desktop-based implementation of our NIHL annotation portal is publicly available on GitHub (https://github.com/GreenCUBIC/AudiogramDigitization).
