论文标题
用于数字接触跟踪的机器学习方法：TC4TL挑战
A Machine Learning Approach to Digital Contact Tracing: TC4TL Challenge
论文作者
论文摘要
接触跟踪是一种公共卫生组织使用的一种方法，可以试图防止社区中传染病的传播。传统上，手动接触示踪剂执行，最近，应用程序的使用被认为使用电话传感器数据来确定两台手机之间的距离。在本文中，我们研究了使用蓝牙低能，感觉数据和元数据来确定两个移动电话设备之间的距离的开发。我们使用TableNet架构和功能工程来改进现有的最新状态（总NDCF 0.21 vs 2.08），大大超过了现有模型。
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.
