Grants and Contributions:
Title:
Acceptability of explainable machine learning based decision support tools in a clinical environment
Agreement Number:
965532
Agreement Value:
$107,996.00
Agreement Date:
Mar 1, 2021 - Mar 1, 2022
Description:
The urgency of the COVID-19 pandemic has triggered a surge in the development of algorithms that address forecasting, contact tracing, screening, and treatment of COVID-19 positive patients to aid clinicians in their decision-making. However, a common feature of this work is a concern that bias in the models may mean the results do not generalize well. Moreover, such models can present challenges to identifying the underlying functional mechanism by which predictions are made and, ultimately, when they do not perform to expectation. Taken together, these issues can present significant challenges to moving such methods into clinical practice.
This Project will seek to demonstrate that user-centric development, when combined with explainable approaches to machine learning can result in greater uptake of new data-driven aids to care by clinicians. This will be done through development of best practices for introducing explainable machine learning (ML) into clinical informatics applications and a validation of these approaches in a prototype presentation layer using an explainable ML analysis that is relevant to clinical needs during pandemics as a test case.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Montreal, Quebec, CA H3T 1E2
Reference Number:
172-2020-2021-Q4-965532
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
130104466
Recipient Type:
Government
Recipient's Legal Name:
Sir Mortimier B. Davis Jewish General Hospital
Federal Riding Name:
Mount Royal
Federal Riding Number:
24052
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
NAICS Code:
541710 - R&D in the physical, engineering and life sciences