论文标题
智能肺炎检测和整合的方法
An Approach to Intelligent Pneumonia Detection and Integration
论文作者
论文摘要
每年，超过250万人（其中大多数在发达国家）死于肺炎[1]。由于许多研究证明，在及时诊断时可以成功治疗肺炎，因此已经开发了许多基于AI的方法来达到高精度[2]。但是，目前，由于概括了本地实现的结果，尤其是在肺炎检测中使用AI的肺炎检测是有限的。在本报告中，我们提出了一个路线图，用于创建和集成试图解决这一挑战的系统。我们还通过可能的解决方案的蓝图解决了各种技术，法律，道德和后勤问题。
Each year, over 2.5 million people, most of them in developed countries, die from pneumonia [1]. Since many studies have proved pneumonia is successfully treatable when timely and correctly diagnosed, many of diagnosis aids have been developed, with AI-based methods achieving high accuracies [2]. However, currently, the usage of AI in pneumonia detection is limited, in particular, due to challenges in generalizing a locally achieved result. In this report, we propose a roadmap for creating and integrating a system that attempts to solve this challenge. We also address various technical, legal, ethical, and logistical issues, with a blueprint of possible solutions.
