Grant: Alliance Grants
The University of British Columbia
$99,000.00
Next generation machine learning technologies for democratizing healthcare through point of care ultrasound
FY 2023-24
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, we have developed IN-POCUS, Intelligent Network for POCUS, in BC. By deploying 80+ POCUS devices across the province, we are now able to provide ultrasound technology to frontline physicians at these critical pandemic times.This NSERC Alliance project is to tackle two of the key challenges we face today in integrating machine learning technologies within IN-POCUS for routine clinical decision making: 1) We require solutions where we can continuously learn from data; and 2) We need to mitigate risk to patients by alleviating silent failure common to machine learning technologies today. Through partnership with Canada's leading POCUS manufacturer, Clarius Mobile Health, world leading medical imaging solutions provider, Change Healthcare Canada Company, and in coordination with IN-POCUS through Providence Healthcare, Vancouver General Hospital, and Rural Coordination Centre BC, we propose to tackle these challenges. We anticipate that machine learning technologies developed will not only have direct impact on IN-POCUS, but they will have broad impact on the entire discipline of machine learning in healthcare, where speed to deployment while mitigating risk is critical. The Alliance project will train 2 PhD, 2 MSc, 5 undergraduate students, and a Research Associate. These HQP will work directly with project partners to establish requirements, develop prototypes and validate solutions in a rapid cycle with end-users to lead the global impact on patient care.
Program
Alliance Grants
Recipient
Location
British Columbia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
556820-2020
Name nom
Abolmaesumi, Purang P
Department département
Electrical and Computer Engineering
Organization id
2
Institution établissement
The University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2020
Award amount
99000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1101
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Human health (including medically-related psychological research)
Area of application fr
Santé publique (y compris recherche psychologique liée à la médecine)
Research subject code
1900
Research subject group en
Biomedical engineering
Research subject group fr
Biomedical engineering
Research subject en
Génie biomédical
Research subject fr
Génie biomédical
Application title
Next generation machine learning technologies for democratizing healthcare through point of care ultrasound
Keyword
Biomedical engineering; Healthcare; Imaging network; Machine learning; Medical imaging; Rural regions; Ultrasound
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, we have developed IN-POCUS, Intelligent Network for POCUS, in BC. By deploying 80+ POCUS devices across the province, we are now able to provide ultrasound technology to frontline physicians at these critical pandemic times.This NSERC Alliance project is to tackle two of the key challenges we face today in integrating machine learning technologies within IN-POCUS for routine clinical decision making: 1) We require solutions where we can continuously learn from data; and 2) We need to mitigate risk to patients by alleviating silent failure common to machine learning technologies today. Through partnership with Canada's leading POCUS manufacturer, Clarius Mobile Health, world leading medical imaging solutions provider, Change Healthcare Canada Company, and in coordination with IN-POCUS through Providence Healthcare, Vancouver General Hospital, and Rural Coordination Centre BC, we propose to tackle these challenges. We anticipate that machine learning technologies developed will not only have direct impact on IN-POCUS, but they will have broad impact on the entire discipline of machine learning in healthcare, where speed to deployment while mitigating risk is critical. The Alliance project will train 2 PhD, 2 MSc, 5 undergraduate students, and a Research Associate. These HQP will work directly with project partners to establish requirements, develop prototypes and validate solutions in a rapid cycle with end-users to lead the global impact on patient care.