By 2027, the health-care AI market is expected to hit $51.3 billion USD, according to a 2020 report published by Meticulous Research. This will be driven in part by the increasing accessibility and rapid growth of heavy computing power, which enables the high demands of a common form of health-care AI: machine learning.
As the name implies, machine learning is a form of AI that echoes how humans absorb and process information. The AI is fed large amounts of data and, using complex algorithms, begins to not just learn from it, but know what to do with it. It can recognize patterns, offer predictions, categorize and detect anomalies in ways — and at volumes — that humans can’t. What’s more, as it does all of that, it continues to learn, refining and improving its abilities.
What’s driving a wave of AI health innovations isn’t just the increasing sophistication of AI technology, however. It’s also human ingenuity. “AI is a tool — it’s up to human researchers to find the applications,” says Mojtaba Hasannezhad, a Concordia PhD candidate in electrical and computer engineering working on AI-based assistants to help the elderly. “We have to be able to come up with the ideas of where we can use these amazing and advanced technologies.”