Title:
AI-Augmented patient-driven fracture risk prediction
Agreement Number:
1028862
Agreement Value:
$75,000.00
Agreement Date:
Feb 1, 2025 - Sep 20, 2025
Description:
The Project will support pilot testing of AI strategies, determine target architecture and quantitative technical objectives for implementation of an AI solution to allow x-ray patients over 50 years of age to predict their risk of future fracture. It will build upon an existing opportunistic AI software medical device approved in Canada which has been in use for over 2 years.
Organization:
National Research Council Canada
Expected Results:
The NRC IRAP Artificial Intelligence (AI) Assist Program aims to equip and support SMEs to incorporate AI into their core products and services and/or undertake scientific research, product development, testing, and validation. AI Assist aims to increase the number, the quality, and the competitiveness of Generative AI (Gen AI), Deep Neural Nets (DNN), and Deep Learning (DL) products created and delivered by SMEs.
Location:
Toronto, Ontario, CA M5J 2N8
Reference Number:
172-2024-2025-Q4-1028862
Agreement Type:
Contribution
Report Type:
Grants and Contributions
Recipient Business Number:
746935923
Recipient Type:
For-profit organization
Recipient's Legal Name:
16 Bit Inc.
Federal Riding Name:
Spadina--Fort York
Federal Riding Number:
35101
Program:
Industrial Research Assistance Program – AI Assist
Program Purpose:
The NRC IRAP Artificial Intelligence (AI) Assist Program aims to equip and support SMEs to incorporate AI into their core products and services and/or undertake scientific research, product development, testing, and validation. AI Assist aims to increase the number, the quality, and the competitiveness of Generative AI (Gen AI), Deep Neural Nets (DNN), and Deep Learning (DL) products created and delivered by SMEs.
Coverage:
The AI Assist program is designed to help innovative SMEs navigate the challenges of developing and adapting generative AI (GenAI) and deep learning (DL) solutions and to assist SMEs with awareness, planning and execution in order to develop these technologies safely and ethically.