RAPID: A Platform for Mitigating the Impacts of COVID-19 on the Healthcare System

这一新冠肺炎快速研究计划将重点解决基本医疗用品、个人防护装备和关键医疗技术短缺的问题。对专业医疗保健的需求激增也造成了熟练的医疗专业人员的短缺，这些专业人员能够操作高科技机器，同时保护自己和他人免受这种危险病毒的侵害。因此，为护理人员提供快速培训并增加个人防护装备和医疗技术的供应是抗击这一史无前例的大流行病的当务之急。该项目将利用国家科学基金会融合加速器项目目前正在开发的研究和技术，为照顾者提供易于使用和访问的培训应用程序，以及在利益攸关方之间解决问题的联网能力。该项目还将在医疗保健社区、医疗设备制造商和经销商以及草根阶层之间建立和促进伙伴关系，在努力提高人们对该项目及其新颖功能的认识的同时，迅速部署原型。该项目的具体目标是为处于抗击新冠肺炎第一线的医疗保健专业人员、护理人员和技术人员提供培训支持、解决问题的资源和专业网络，以便进行思想交流。深度学习和自适应自主系统等人工智能技术将用于开发智能知识网络，以支持虚拟社区，以及创建增强现实技术，以提供高效和引人入胜的虚拟培训。因此，该项目的研究目标包括：1)为新冠肺炎大流行的护理人员和技术人员开发一个增强现实培训移动应用程序；2)部署一个在线设备解决问题资源储存库；3)开发一个专业网络应用程序，以传播抗击新冠肺炎的研究和最佳做法，供所有参与应对这一流行病的利益攸关方使用。该项目的总体重点是创建一个具有移动增强现实功能的网络应用程序，用于随时随地培训医疗保健专业人员，以改善使用医疗设备进行培训的机会，并提高安全培训的效率和覆盖范围。该项目团队将在创建人工智能支持的增强现实培训时推进计算机科学和空间计算方面的知识库。该团队将通过相关的学术会议和杂志传播其发现和技术。这一快速奖项由综合活动办公室的融合加速器计划利用冠状病毒援助、救济和经济安全法案(CARE)的资金颁发，并与融合加速器轨道B：人工智能与未来就业和国家人才生态系统相关。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This COVID-19 RAPID research program will focus on addressing the shortage of essential medical supplies, Personal Protective Equipment, and crucial medical technologies. A surge in demand for specialized healthcare has also created a shortage of skilled medical professionals capable of operating highly technical machines while protecting themselves and others against this dangerous virus. Thus, providing rapid training for caregivers and increasing the supply of Personal Protective Equipment and medical technology is an immediate priority for combating this unprecedented pandemic. This project will leverage the research and technology currently under development in a National Science Foundation Convergence Accelerator project to provide an easy to use and access training application for caregivers, as well as networking capacity for problem-solving among stakeholders. This project will also build and foster partnerships among the healthcare community, medical equipment manufacturers and distributors, and grassroots efforts to rapidly deploy prototypes as it strives to create awareness of the project and its novel features.The specific goals of this project are to provide training support, problem-solving resources, and professional networking for idea exchanges for healthcare professionals, caregivers, and technologists that are on the frontlines in the fight against COVID-19. Artificial Intelligence techniques such as deep learning and self-adaptive autonomous systems will be used to develop an intelligent knowledge network to support virtual communities, as well as, create Augmented Reality technologies for delivering efficient and engaging virtual training. Thus, the research objectives of this project include: 1) development of an Augmented Reality training mobile application for caregivers and technologists responding to the COVID-19 pandemic; 2) deployment of an online repository for equipment problem-solving resources; and 3) development of a professional networking application to disseminate research and best practices in the fight against COVID-19 for all stakeholders engaged in addressing the pandemic. The project's overarching focus is to create a web application with mobile Augmented Reality capability for training healthcare professionals at any location and time, in order to improve access to training with the medical equipment and increase the efficiency and reach of safety training. The project team will advance the knowledge base in computer science and spatial computing as it creates its Artificial Intelligence-powered Augmented Reality training. The team will disseminate its findings and technology through relevant scholarly conferences and journals.This RAPID award is made by the Convergence Accelerator program in the Office of Integrative Activities using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act, and is associated with the Convergence Accelerator Track B: Artificial Intelligence and Future Jobs and National Talent Ecosystem.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.