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Founded in 2012 by Alexandre Le Bouthillier and Nicolas Chapados in collaboration with Yoshua Bengio, Imagia contributes to Quebec’s artificial intelligence sector’s growth and prominence. The company, which now has 60 employees, wants to set itself apart while bringing tangible added value to the applications developed by artificial intelligence.

Cutting-edge mentality 

Its unique and friendly collaborative spirit is what makes Imagia stand out. Its founders firmly believe that the entire ecosystem should shine and develop useful applications so that the greatest number of people can benefit from breakthroughs in artificial intelligence. Their vision incorporates the global success of all the sector’s stakeholders. 


Concrete goals

There is no doubt that artificial intelligence can help improve health care. The Imagia team’s primary goal is to leverage data in order to make new discoveries and bring innovation directly to the patient. Its work focuses on developing medical applications that benefit patients, researchers, pharmaceutical companies, medical device manufacturers, physicians, and the government.  


Skyrocketing healthcare costs: an issue to consider 

Healthcare costs are skyrocketing due to our aging population and the fact that medical breakthroughs take a very long time to fully materialize and are extremely expensive. Imagia wants to help accelerate discovery while reducing expenses and improving patient care.

Diagnosing a disease is a long, complex, invasive, and costly process: blood tests, sample collection, questionnaires, physical exams, etc. Even once these tests have been completed, the diagnosis can still be disputable, with treatments being administered with no guarantee of success. Improving diagnoses and therapeutic choices for patients is one of Imagia’s objectives.


Artificial intelligence’s contribution to precision diagnostics 

Artificial intelligence is bringing a paradigm shift in medical care by:

– accelerating routine data acquisition in a non-invasive way

– combining several types of data (environmental, genomic, and pathology and imaging reports)

– providing a complete picture of the patient’s profile

The models produced by artificial intelligence allow for connections to be made between a patient’s various data so that the right tests are prescribed; this increases the chances of an accurate diagnosis of their disease. As a result, the best treatment is chosen more quickly, and with fewer trial-and-error approaches being used, patient recovery is faster. Artificial intelligence is the basis of personalized medicine: with each individual being unique, they must be treated in a personalized way for optimal results to be achieved. 


Imagia’s EVIDENS™ AI platform    

Imagia created an innovative platform to support diagnoses and treatment choices: EVIDENS. Already being used by clinical researchers in various Quebec hospitals, this technology facilitates discovery by integrating patient data into a computerized algorithm. This model helps to explain why a particular treatment did or did not work, therefore contributing to advancing medical research (For more information).   


Protecting personal information while fostering discoveries

Privacy and data sharing are sensitive issues around the world. Imagia’s EVIDENS™ platform is based on a model that minimizes the risk of leaks by focusing on the discovery component rather than on the data. Personal information remains within the hospital itself and is only used to feed the algorithm: only the resulting discoveries are shared. 


Good news for the company

Imagia’s EVIDENS™ platform has been very successful, and discussions are underway to implement the platform in various countries. Imagia is also part of an impressive Canadian consortium of 97 partners that has the support of the federal government to develop the Digital Discovery and Health Platform (DDHP). This platform combines Canada’s expertise in artificial intelligence and precision medicine to deliver better health care to Canadians. The EVIDENS™ platform will be used in this most critical personalized medicine project (For more information).