论文标题
自动化问题答案基于深度学习技术的医疗模型
Automated Question Answer medical model based on Deep Learning Technology
论文作者
论文摘要
人工智能现在可以为不同问题提供更多解决方案，尤其是在医疗领域。这些问题之一是缺乏任何给定医疗/健康相关问题的答案。互联网上到处都是论坛，使人们可以提出一些特定的问题并为他们获得很好的答案。然而，浏览这些问题以找到与您自己的问题相似的问题，也找到令人满意的答案是一项艰巨而耗时的任务。这项研究将通过自动化这些问题的合格答案并创建一种数字医生来引入解决此问题的解决方案。此外，这项研究将使用RNN和编码器编码器的框架训练端到端模型，从而为一系列的医疗/健康问题提供明智而有用的答案。使用来自WebMD，HealthTap，Ehealthforums和Icliniq等各种在线服务的数据对所提出的模型进行了培训和评估。
Artificial intelligence can now provide more solutions for different problems, especially in the medical field. One of those problems the lack of answers to any given medical/health-related question. The Internet is full of forums that allow people to ask some specific questions and get great answers for them. Nevertheless, browsing these questions in order to locate one similar to your own, also finding a satisfactory answer is a difficult and time-consuming task. This research will introduce a solution to this problem by automating the process of generating qualified answers to these questions and creating a kind of digital doctor. Furthermore, this research will train an end-to-end model using the framework of RNN and the encoder-decoder to generate sensible and useful answers to a small set of medical/health issues. The proposed model was trained and evaluated using data from various online services, such as WebMD, HealthTap, eHealthForums, and iCliniq.
