Case Study

Clinisys EMR aiming for a collaborative AI revolution in healthcare

Artificial intelligence (AI) and machine learning could be revolutionary in increasing the quality and availability of healthcare, according to Mehadi Sayed, the founder of the electronic medical records company Clinisys EMR Inc. But achieving that ambitious goal will require close cooperation and collaboration among private industry, educational and research institutions, as well as all levels of government.

"Machine learning models ... can improve diagnosis. It can improve patient wait times, improve patients' quality of life, and so forth," says Sayed.

Clinisys has spun off a new, machine-learning focused health analytics company, Clinilytics. The new organization was born out of a trend that Sayed noticed during his career as a technology educator and running a company that specializes in digital health information. For the past decade, he says, there has been a sharp focus on collecting data -- not just in the health and wellness industries but also across sectors from financial services to manufacturing. However, collecting data is only the beginning; you need to know how to use it effectively. Clinilytics uses machine learning, artificial intelligence and data analytics to build tools for healthcare providers: doing everything from better managing resources to administrative tasks, to aiding with diagnostics.

Recently, the company played an important role in a collaborative project designed to bring together nine organizations in Alberta working on innovative AI-driven projects. The initiative, part of the Western Economic Diversification Canada Regional Innovation Ecosystems (RIE) program, aimed to help the Alberta-based health and wellness organizations research viable uses for artificial intelligence and machine learning in health and data analytics.

For many of the organizations, it was the first time they had begun developing AI-enabled products. Clinilytics offered guidance, providing analysis and its expertise in machine learning to the organizations developing their pilot projects. Sayed says the results were surprising; research and development work always comes with a high risk of failure, but all of the ecosystem projects saw at least some level of success.

"None of the projects had zero results. Every project had, on the scale of one to ten, success level between seven to nine," he says. "It was very heartwarming to see what impact a collection of companies can make."

Building the ecosystem

The pilot projects aimed to solve a variety of problems. Work done at the Cross Cancer Institute focused on resource management to predict patient numbers and help administrators better prepare staff, equipment, and medication. Meanwhile, a project in collaboration with the Canadian Sport Institute Calgary focused on gathering sensory experiences of elite athletes to develop the next generation of wearable technology.

Another project made steps toward helping clinicians make more accurate diagnoses: Calgary's CardiAI is developing AI tools to predict anomalies in heart rhythms and cardiac imaging.

That culture of cooperation and collaboration, instead of competition, will be an essential part of continuing to build a strong ecosystem in Alberta, Sayed argues. Healthcare and artificial intelligence are both fast-moving fields. Any lessons learned by one organization can be invaluable to other companies down the road who might encounter the same hurdles.

"Projects such as these definitely move the entire ecosystem in a positive direction," he says.

“We have just started right now, but we already see inquiries from other jurisdictions and companies with similar data sets. They want to explore the data and repurpose it. So we are sharing this resource with a wider community."

Collaboration also helps counter the main challenge that Sayed sees facing any organization working in artificial intelligence: access to talent. With so much attention placed on AI and its potential, the demand for people who can build these tools far outstrips the supply. Sharing resources and expertise can be a big help. He notes that Alberta-based companies have a massive advantage in that particular area, with access to institutions like Amii that attract experts and train talented workers in the province.

"Sure, we need private companies, but we also need institutions such as Amii. We need educational institutions such as the University of Alberta, the University of Calgary and many others. At the same time, we also need the support from the government."

This project was part of the Western Economic Diversification Canada Regional Innovation Ecosystems (RIE) program. The initiative brought together nine organizations from non-profit, business and academia to establish viable uses for artificial intelligence and machine learning in health and data analytics.

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