If you’ve wondered what artificial intelligence can do for you, think of the time you’ve wasted in a doctor’s waiting room.

A Quebec tech company said it can cut wait times to under 20 minutes and save patients 6.5 million hours a year in the province alone.

Bonjour-Santé, which manages bookings for more than 300 clinics in Quebec, teamed up with Montreal’s flagship AI lab to create an algorithm predicting delays. The model looks at tens of thousands of past appointments through 1,900 parameters — from the weather to the type of medical-file software the doctor uses. Two hours before the scheduled time, patients receive a text estimating when the doctor will actually see them.

The service is currently offered at 10 clinics in the Bonjour-Santé network at no additional charge. Founder Benoit Brunel said potential paying clients include hospitals and eventually, other industries struggling with needless waits.

“People are always looking for time, it’s the most valuable thing in life,” Brunel said in an phone interview. “We’re in the very early days. I have at least 20 projects I’d like to start.”

Businesses could create as much as $5.8 trillion in value per year globally adopting deep learning techniques — a subset of machine learning that’s inspired by the structure of the brain — according to a study by the McKinsey Global Institute. Yet the shift is only starting and complicated by one condition not all companies can meet: It takes a lot of data to train an algorithm and determine which model works best.

Enter the medical field, where a treasure trove of information including blood-pressure readings, lab results and doctor’s notes are spurring companies to develop new strategies for improving efficiency and saving lives. Microsoft Corp. for example, is exploring how it can use AI to detect early warning signs of disease, while Google in May published a paper on an AI system that would provide a score on how likely a patient is to die based on almost 50 billion pieces of data.

For its part, Bonjour-Santé had a data set of 1.2 million appointments to start working with MILA-Quebec Artificial Intelligence Institute, the centre that has contributed to making Montreal one of the world’s AI hubs under under the leadership of neural networks pioneer Yoshua Bengio. A group of experts there mentors selected companies under a technology-transfer program, with a focus on innovation “that is good for human beings,” Myriam Côté, who heads the government-subsidized initiative, said in an email.

Bonjour-Santé carved out a niche helping people score an appointment at a walk-in clinic in its home province. The platform, which some have criticized for introducing two tier health-care, is free for doctors but charges patients $17.25 for a search outside of their usual clinic. It’s part of closely held Tootelo Innovation Inc., a company founded and headed by Brunel that offers customer-service and emergency-response outsourcing.

Brunel, who owns 68 per cent of Tootelo, said he’d consider going public if there was a sudden surge in demand but has no immediate plan to do so.

The company previously tried to estimate delays using traditional statistical methods and a handful of criteria but couldn’t lower the average wait below 45 minutes, according to Pierre Lafrance, who’s leading the project. In deep learning, data are repeatedly run by models, which can detect patterns — for instance, a doctor’s tendency to be late on a given day. Data keep being added, too.

"People are always looking for time, it's the most valuable thing in life,"

- Benoit Brunel, founder, Bonjour-Santé

At Polyclinique Levasseur, a Montreal facility that’s using the new program, director Julie Lessard says she’s been able to add doctors without facing a corresponding surge of people — and germs — in the waiting room

“It’s very positive for us,” she said. “When people get into the consultation, they haven’t been here for two hours, chomping at the bit.”

Brunel says the algorithm could be exported to other provinces, where it has about 50 clients, or to countries with similar health-care systems. Even in the U.S., a 2016 survey showed that 63 per cent of patients find the wait in the lobby the most stressful part of going to the doctor.

Already, Lafrance is mulling the addition of new parameters to improve the algorithm, including a very local one: The game schedule for the Montreal Canadiens.

“It’s less busy when the Canadiens play,” Lafrance said. “Some clinics can literally be short on patients to fill the slots.”

— With assistance from Doug Alexander.

This article originally appeared in Financial Post