Scale AI funds two MUHC AI projects aimed at improving cardiac imaging services and nursing staff management

These initiatives are being developed in close collaboration with IvadoLabs and Airudi to accelerate the integration of responsible AI-driven solutions across the healthcare system.
 

The McGill University Health Centre (MUHC) has received funding from Scale AI to advance two major initiatives that aim to improve access to care, streamline operations and support frontline teams.
 

Project 1: EchoAccess, transforming cardiac imaging scheduling in partnership with IvadoLabs

More than 10,000 patients require an echocardiogram each year at the MUHC. To improve access and efficiency, the MUHC is leading an initiative to modernize and optimize echocardiography scheduling across its network.

The EchoAccess project will deploy a four-component AI solution designed to

• automate triage
• predict appointment durations
• assess the risk of no-shows
• prioritize exams based on clinical urgency

Together, these tools aim to reduce unnecessary imaging, improve the use of clinical resources and accelerate access to diagnoses.

“Echo-Access is designed to minimize unnecessary imaging, optimize existing resources, and enhance patient care pathways,” explains Dr. Francois Tournoux, Director of the Echocardiography Laboratory, who leads this initiative with his multidisciplinary team at MUHC (Bintou Diawara, Dr. Tara D’Ignazio, Lucrèce Francois, Nadia Guerrera and Irene Voron Kostychuk). 

“Access to cardiac imaging is crucial, as it enables early and accurate diagnosis of serious conditions. It guides effective, personalized treatment and ongoing monitoring, ultimately improving outcomes and preventing major events,” says Georgia Niarchos, Director of Perioperative and Imaging Services for the adult sites at the MUHC. 

Project 2: ENACT, an AI-powered solution to support nursing teams, developed in collaboration with Airudi

Hospitals are facing a critical nursing workforce crisis marked by high staff turnover, excessive overtime and the closure of essential-care beds. A major contributor to this strain is the time nurses must devote to non-clinical tasks such as documentation, coordination and manual scheduling.

The ENACT project, developed in collaboration with the Montreal-based company Airudi, introduces a suite of artificial intelligence-based tools to address these challenges. By using predictive models and multi-task learning, ENACT will

• optimize staff assignments
• automate shift reports
• support the prioritization and delegation of nursing interventions

This approach will enable nurses to spend more time on direct patient care (at least one additional hour per week per nurse) and improve work-life balance, while supporting a more resilient and efficient healthcare system.

Development is guided by nursing expertise to ensure the tools are practical, relevant and aligned with the realities of clinical practice. Designed for gradual deployment across hospital sites, the solution adapts to diverse clinical settings to ensure lasting impact.

“ENACT is a project for nurses, by nurses. It integrates artificial intelligence solutions and equips teams with powerful tools to support their work, while allowing them to focus on what really matters, spending more time with their patients,” says Alain Biron, Director of Nursing, MUHC, who is leading this initiative with Jasmine Hill and Paule Jubinville. “We are proud to be part of this unique collaborative initiative, made possible thanks to the support of the Montreal General Hospital Foundation and Scale AI.”