数字接触追踪的机器学习方法：TC4TL挑战
A Machine Learning Approach to Digital Contact Tracing: TC4TL Challenge
摘要：
接触者追踪是公共卫生组织用来防止传染病在社区传播的一种方法。传统上由手动接触追踪器执行，最近已考虑使用应用程序利用手机传感器数据来确定两部手机之间的距离。在本文中，我们研究了机器学习方法的发展，以确定使用蓝牙低功耗，传感器数据和Meta数据的两个移动电话设备之间的距离。我们使用TableNet架构和功能工程来改进现有的最新技术水平（总nDCF为0.21 vs 2.08），显著优于现有模型。
英文摘要：
Contact tracing is a method used by public health organisations to try prevent the spread of infectious diseases in the community. Traditionally performed by manual contact tracers, more recently the use of apps have been considered utilising phone sensor data to determine the distance between two phones. In this paper, we investigate the development of machine learning approaches to determine the distance between two mobile phone devices using Bluetooth Low Energy, sensory data and meta data. We use TableNet architecture and feature engineering to improve on the existing state of the art (total nDCF 0.21 vs 2.08), significantly outperforming existing models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
