Canada emerging as global hub for healthcare AI

There are growing signs that Canada is emerging as a global hub of expertise in AI for medicine and healthcare applications. A number of innovative projects and technologies have been launched in this area in recent months – and several observers predict there is considerable potential for continued expansion.


In recent years, Canada has nurtured a strong reputation as a global centre for AI research and development and cemented its position as a pioneer in this area through the establishment of world-renowned centres of excellence such as MILA and AMII, as well as the Vector Institute in Toronto. Building on this success, there are now growing indications that the country is also becoming a global leader in AI for medicine and healthcare applications.

A great deal of this progress is being spearheaded by universities, through initiatives like the recently established Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM). As Muhammad Mamdani, Director at T-CAIREM and professor at the University of Toronto, which hosts the Centre, explains, the Centre aims to: establish a leading education program in applied artificial intelligence for medical and health science professionals; create a robust health data environment ‘enabling timely access to high quality health data to fuel innovation and quality improvement and support education programs’; and foster multidisciplinary, collaborative research in artificial intelligence in medical and health sciences and ‘encourage clinical translation.’ In moving towards these goals, T-CAIREM has three themes - Education, Research, and Infrastructure - each linked to a range of key outputs (see Table 1).

Table 1: T-CAIREM – Key Themes and Outputs





· Launch of Speaker Series featuring prominent leaders in AI in Medicine in January 2021;

· Launch of set of trainee rounds bringing together students in numerous disciplines including medicine, computer science, statistics, and engineering;

· Provision of 14 studentships in summer 2021;

· Coordination of structured training materials for a variety of learners, including beginners, intermediate learners, and advanced learners in 2022;

·  Establishment of mentorship program in late 2021.


·  Two $200K grants offered for research initiatives focusing on transformative ideas in AI in medicine (over 60 applications received, with awards scheduled for autumn 2021).


· Develop robust 'collaborative' data environment on Amazon Web Services to enable researchers to easily access large datasets and share data (scheduled for full functionality in early 2022).

· Build community by establishing several forums where members can post ideas and ask for collaborators, as well as set up interest groups.

In Mamdani’s view, there is ‘considerable’ long-term potential for Canada to develop as a globally significant centre of expertise in medical and healthcare AI – particularly in view of the fact that the country has ‘several key, world class centres for AI including the Vector Institute, MILA, and AMII.’

“I believe federal, provincial, and local investments will continue to grow in this area. One challenge is the coordination of efforts locally and nationally - AI is driven by data and culture. While there are initiatives locally and nationally to consolidate large datasets, the timeliness of data becomes important for actual implementation purposes and comprehensive real-time datasets aren't widely available,” he says.

“IT professionals could very much drive the assimilation of large, real-time datasets. Further, issues of privacy and security as well as data governance are paramount. Data modelers, data architects, data engineers, and ETL developers, to name a few, would be incredibly valuable,” he adds.

‘Foundational Provenance’

Another interesting recent development has been the establishment of the Roche AI Centre of Excellence, set up by Roche Canada to act as a platform to coordinate internal and external engagement activities aimed at addressing big challenges in healthcare.

As Fanny Sie, Head of Artificial Intelligence and Digital Health at Roche Canada, explains, a key motivation for the establishment of the Centre was the learning experienced gained from the Roche COVID-19 Data Science Coalition (RDSC), which enabled it to accelerate the time it took to develop digital health solutions and insights – and shorten the time needed to bring them to market.

“We therefore wanted to reproduce this model in other therapeutic areas and developed the AI CoE around the same operating model.

According to Sie, the AI CoE is currently ‘exploring its focus on oncology, neurodegeneration and rare conditions in addition to the expansion of its work in COVID-19.’ The RDSC has also developed ‘over 100 digital solutions and insights, including AI models, advanced analytics, virtual dashboards, and market reports since its formation.’

“The AI CoE is set to use the RDSC’s framework for cross-sector collaborations in order to drive digital transformation in Canada’s healthcare system,” says Sie.

Moving forward, Sie also believes there is a strong potential for Canada to develop as a globally significant centre of expertise in medical and healthcare AI – building on what she describes as the country’s ‘foundational provenance in AI with the rise of the ‘godfathers’ of machine learning - Geoffrey Hinton and Yoshua Bengio - and the most cited scientist in reinforcement learning, Richard Sutton.’

“Each has a dedicated research institute housed in Ontario, Quebec and Alberta, respectively, which have provincial, federal and industry partnerships working together on the most progressive initiatives in AI,” she says.

“Canada has the ability to elevate in building the foundations of a knowledge economy and build learning health systems focused on delivering access to healthcare in the most efficient and effective way. This capability-building may then be scaled to healthcare systems globally,” she adds.

However, if Canada is to realise its ‘vision’ of becoming a globally significant healthcare AI hub, Sie stresses the key importance of ensuring its IT professionals are equipped with cross-sectional expertise in applied AI.

“The ability of the community to leverage scientific innovations will depend on its ability to communicate across multidisciplinary teams and mobilize knowledge for patient benefit at scale,” she says.

‘Trailblazing Mavericks’

Elsewhere, medtech outfit Skinopathy has created an innovative AI-based skin cancer screening tool using Convolutional Neural Network (CNN) technology. As Richard Pietro, Lead Writer at Skinopathy, explains, CNN’s are mostly used for analysing images - with the most famous application being the ‘Re-Captcha’ security feature found on many websites, which is a process that trains such CNNs. 

“However, instead of using our AI to determine the difference between a fire hydrant and a bus, we are using this technology to determine the difference between a mole and a cancerous lesion,” says Pietro.

In order to ‘future-proof’ the technology for other use-cases, Pietro reveals the company is focused on refining two key development pathways. The first is a ‘narrow’ approach, used solely for classifying skin abnormalities – a proprietary light-load AI that will allow for ‘super accurate identification of skin abnormalities while being less computationally intensive.’ The second is a ‘broad’ approach used for classifying everyday objects.

“This will be a computationally-expensive but generalized CNN, whose code will be open-sourced at a later date. This will allow non-commercial researchers, or licensed commercial users, to adapt our AI model’s architecture and optimization strategies for other specific use cases,” says Pietro.

For Pietro, the long-term potential for the expansion of this sector in Canada is ‘very favourable’ – at least in part because of ‘exceptional higher-learning institutions who understand the value of technological breakthroughs and are dedicated to moulding brilliant young minds.’

“This attitude has even trickled to community organizations, such as incubators and accelerators, but also libraries, where coding and robotics are now being taught to teenagers,” he says.

While working with partners at Industry Canada and the National Research Council, Pietro also points out that it has become clear that government officials ‘want nothing more than to position Canada as an international leader in digital health, and are allocating resources, time, and political will to those efforts.’

“Lastly, for several years it seemed like social media was running-the-roost when it came to innovation. Nowadays, Canadian entrepreneurs are looking beyond and want to tackle much more daunting problems, such as healthcare. They have the tools, know-how, and government support to make their mark,” he says.

Speaking ‘strictly from a start-up perspective,’ Pietro also believes that interdisciplinary knowledge and experience are ‘more valuable than ever before.’

“For example, Skinopathy employs physicians who are also marketers; Machine Learning engineers who possess biomedicine degrees; and content creators who are data experts,” he says.

“Complementary skills in diverse fields are essential in the entrepreneurial community. We are always on the lookout for individuals who can do more than one thing very well. It also does not hurt if those individuals label themselves as trailblazing mavericks with a passion for solving wicked problems,” he adds.