8 AI Healthcare Startups with FDA-Approved Algorithms

Originally published in Nanalyze

Last year, investors rode some record highs. The market charged upward, despite The Rona. More investors spazzed out on SPACs, to the tune of nearly 250 IPOs that raised about $80 billion. That’s about as much funding ($80.6 billion) that was funneled into global healthcare startups in 2020. That’s a new record, according to the big brains at CB Insights. AI healthcare startups alone raised $6.6 billion – another record high.

The old adage is that 90% of startups fail within five years, which means most of that money could have been put to better use, like a lost weekend in Cabo with your favorite drug dealer. It’s often difficult to gauge the success of private companies because they generally don’t let the public nose around in the books. Instead, they release meaningless press releases that claim a 100% increase in revenue with no baseline for comparison. 

FDA-Approved Algorithms

One metric to judge how well an AI healthcare startup is delivering the goods – especially in diagnostics or therapeutics – could rely upon whether its platform or medical device has approval or clearance from the U.S. Food and Drug Administration (FDA). The federal agency in charge of regulating everything from hemorrhoidal creams to herpes vaccines, FDA is finally recognizing that AI and machine learning require some different criteria to evaluate safety and effectiveness. We expect that some of the changes underway will accelerate FDA approval of AI algorithms to diagnose and treat disease. There are currently about 60 FDA-approved AI-based algorithms and medical devices, according to a database compiled by The Medical Futurist.

The technology first began to gain real traction in 2018, with only three approvals prior to then. That was the same year we compiled our own list of FDA-approved algorithms. In all, we have written about at least 18 companies whose machine-learning platforms or AI-powered medical devices have gotten the green light from FDA for different kinds of applications. 

FDA-Approved Algorithms for Remote Patient Monitoring

The use of AI to monitor patients remotely is certainly a boon at a time when no one really wants to spend more time than necessary in the hospital. Founded in 2013, Chicago-based PhysIQ has raised $26.4 million to continue cranking out algorithms designed to make better sense of wearable sensor data. It uses a deep neural network to provide cloud-based analytics using a range of physiological data, including heart rate, heart rate variability, atrial fibrillation detection, and respiration rate. Here’s the platform, pinpointIQ, in a format that even an MBA can understand:

In one peer-reviewed research paper, PhysIQ scientists demonstrated that the company’s AI can predict impending heart failure from sensor data as well as an implanted device, which means we can monitor patients without invasive surgery and at much lower costs.

Conclusion

There are now thousands of startups that claim to be developing AI solutions across a dizzying range of applications. It’s often hard to figure out the real deal from the hype. However, when it comes to relying on a piece of software for life and death matters, you want to be sure that it does what it says it does. Algorithms that have FDA approval or clearance are most likely going to be the real deal. That provides the companies themselves a way to stand above the crowd in a much-hyped and competitive space. It’s also one metric retail investors should keep in mind as more opportunities arise to invest in AI healthcare companies.

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