Grant: Alliance Grants
University of British Columbia
$284,000.00
Rising from the pandemic: Towards sustainable development of machine learning technologies for point-of-care Ultrasound Imaging
EF 2021-22
Résumé
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.
Programme
Alliance Grants
Bénéficiaire
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
570487-2021
Name nom
Abolmaesumi, Purang
Department département
Electrical and Computer Engineering
Organization id
2
Institution établissement
University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2021
Award amount
284000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
518
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Medical equipment and apparatus
Area of application fr
Appareils et instruments médicaux
Research subject code
1901
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomedical technology
Research subject fr
Technologie biomédicale
Installment
inst:1; 2
Partie
2
Nb partie
3
Application title
Rising from the pandemic: Towards sustainable development of machine learning technologies for point-of-care Ultrasound Imaging
Keyword
NSERC
Application summary
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.