Rising from the pandemic: Towards sustainable development of machine learning technologies for point-of-care Ultrasound Imaging

从大流行中崛起：致力于床旁超声成像机器学习技术的可持续发展

• 批准号: 570487-2021
• 负责人: Abolmaesumi, Purang
• 金额: $ 20.69万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=723186
• 关键词: Rising; pandemic; Towards; sustainable; development

Point-of-care ultrasound (POCUS) describes the process whereby any healthcare practitioner uses a portable ultrasound device to diagnose conditions at the bedside, whether in an urban hospital, rural clinic, or a remote location. When used appropriately, POCUS can reduce wait times for diagnostic tests, make patient treatment pathways more efficient, streamline transfers to save healthcare costs, and save lives. Although this technology is becoming cheaper and more portable, its use still remains significantly constrained by the high levels of training required by its operators to become proficient in interpretation and analysis. Through $2.5M investment from Canada's Digital Technology Supercluster and our partnership with Clarius Mobile Health, the leading Canadian POCUS manufacturer in Burnaby, BC, we have developed IN-POCUS, Intelligent Network for POCUS, in BC. By deploying close to 100 POCUS devices across the province, we have been able to provide ultrasound technology to frontline physicians at these critical pandemic times. These POCUS devices are augmented with machine learning (ML) technologies from our team at UBC, initially with a focus on cardiac imaging, obstetrics and Covid-19 diagnosis. This NSERC Alliance Missions project is to tackle two of the key challenges Clarius is currently facing in their strategic planning for sustainable development and maintenance of ML technologies in their product line. Specifically, as Clarius devices are deployed broadly across BC and are used by less experienced POCUS operators, there are major concerns in terms of automatic detection of ML failure modes, and continuous learning from new data to ensure models stay current and up-to-date. Timely addressing these challenges will ensure that Clarius maintains its competitive edge globally and sustain its current exponential growth. The Alliance project will train 1 postdoctoral fellow, 4 MSc, 4 undergraduate students, a Research Associate and a clinical fellow. These HQP will work directly with Clarius to establish requirements, develop prototypes and validate solutions in a rapid cycle with clinical end-users to lead the global impact on patient care.

临床点超声(PPoUS)描述了任何医疗从业者使用便携式超声设备在床边诊断病情的过程，无论是在城市医院、农村诊所还是在偏远地区。如果使用得当，Pocus可以减少诊断测试的等待时间，使患者的治疗路径更加高效，简化传输以节省医疗成本，并拯救生命。尽管这项技术正在变得更便宜和更便携，但它的使用仍然受到操作员熟练掌握解释和分析所需的高水平培训的严重限制。通过加拿大数字技术超级集群250万美元的投资，以及我们与不列颠哥伦比省本纳比领先的加拿大Pocus制造商Clarius Mobile Health的合作，我们在BC开发了IN-Pocus，即Pocus的智能网络。通过在全省部署近100台Pocus设备，我们能够在这些关键的大流行时期为一线医生提供超声波技术。这些Pocus设备使用了我们在不列颠哥伦比亚省团队的机器学习(ML)技术，最初专注于心脏成像、产科和新冠肺炎诊断。这个NSERC联盟使命项目是为了解决Clarius目前在其产品线中ML技术的可持续发展和维护的战略规划中面临的两个关键挑战。具体地说，由于Clarius设备在不列颠哥伦比亚省广泛部署，并由经验较少的Pocus运营商使用，因此在ML故障模式的自动检测以及从新数据中持续学习以确保模型保持最新方面存在重大问题。及时应对这些挑战将确保Clarius保持其全球竞争优势，并保持目前的指数增长。该联盟项目将培养1名博士后研究员、4名硕士、4名本科生、1名副研究员和1名临床研究员。这些HQP将直接与Clarius合作，在与临床最终用户的快速周期中建立需求、开发原型和验证解决方案，以引领对患者护理的全球影响。