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.

Point Pary超声波（POCUS）描述了任何医疗保健从业者使用便携式超声设备诊断床边的状况的过程，无论是在城市医院，农村诊所还是偏远位置。当适当地使用时，Pocus可以减少诊断测试的等待时间，使患者治疗途径提高效率，简化转移以节省医疗保健成本并挽救生命。尽管这项技术变得更便宜，更便携，但其使用仍然受到其运营商所需的高水平培训的限制，以精通解释和分析。通过加拿大数字技术超级集体的250万美元投资以及我们与卑诗省本那比的加拿大领先的Pocus制造商Clarius Mobile Health的合作，我们已经开发了卑诗省Pocus的智能网络。通过在全省部署近100个Pocus设备，我们能够在这些关键的大流行时期为前线医生提供超声技术。这些POCUS设备通过UBC团队的机器学习（ML）技术增强，最初是针对心脏成像，产科和COVID-19诊断的。这个NSERC联盟任务项目是应对克拉里斯目前面临的两个主要挑战，目前面临其产品线中ML技术的可持续发展和维护的战略规划。具体而言，由于Clarius设备在卑诗省大部分地区都广泛部署，并且经验不足的Pocus操作员使用，因此在自动检测ML故障模式以及从新数据中进行持续学习以确保模型保持最新和最新时，存在着主要的担忧。及时应对这些挑战将确保克拉里乌斯在全球维持其竞争优势，并维持当前的指数增长。联盟项目将培训1名博士后研究员，4个MSC，4位本科生，一名研究助理和一名临床研究员。这些HQP将直接与Clarius合作，以建立需求，开发原型并在临床最终用户的快速周期中验证解决方案，从而引发全球对患者护理的影响。