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.

医疗点超声（POCUS）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，使患者的治疗途径更有效，简化转移以节省医疗成本，并挽救生命。尽管这项技术变得越来越便宜和便携，但它的使用仍然受到操作员需要进行高水平培训才能熟练掌握解释和分析的限制。通过来自加拿大数字技术超级集群的250万美元投资，以及我们与位于卑诗省本拿比的加拿大领先POCUS制造商Clarius Mobile Health的合作，我们在卑诗省开发了in -POCUS，即POCUS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技术。我们UBC团队的机器学习（ML）技术增强了这些POCUS设备，最初专注于心脏成像、产科和Covid-19诊断。该NSERC联盟任务项目旨在解决Clarius目前在其产品线中可持续发展和维护ML技术的战略规划中面临的两个关键挑战。具体来说，由于Clarius设备在BC省广泛部署，并且由经验不足的POCUS操作员使用，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状态方面存在主要问题。及时应对这些挑战将确保Clarius在全球保持竞争优势，并保持目前的指数增长。联盟项目将培养1名博士后、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，与临床最终用户一起建立需求，开发原型并验证解决方案，从而在全球范围内对患者护理产生影响。