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First FDA-cleared autonomous AI makes new moves in healthcare diagnostics

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In 2018, Iowa-based Digital Diagnostics made headlines when it became the first autonomous AI (artificial intelligence) system authorized by the U.S. Food and Drug Administration. It received FDA approval to use AI to autonomously detect diabetic retinopathy in adults with diabetes, without the need for input from a doctor. 

Its AI-diagnostic system, the IDx-DR, can be used to identify diabetic retinopathy – one of the leading causes of blindness in the U.S. and other developed countries – as well as other serious eye diseases, including macular edema. 

“There’s a strong mission and purpose for us to get our technology to patients that really need to be tested, and certainly to providers that may be burnt out or are getting burnt out,” Seth Rainford, cofounder, president and COO of Digital Diagnostics, told VentureBeat.

In an effort to help get its technology to market and fulfill its mission of “paving the way for AI diagnosis to become a standard-of-care, democratizing healthcare and closing care gaps,” Digital Diagnostics today announced that it has raised $75 million in a series B funding round. 

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The need for AI automation in eye care

The original idea for Digital Diagnostics came from the company’s founder Dr. Michael Abramoff, Rainford explained.

Dr. Abramoff, retina specialist, also has advanced degrees in machine learning. While working as a practicing physician, he often had patients coming in who had been waiting for months to get a routine exam to see if they were losing their eyesight. It was obvious to Dr. Abramoff that there was a gap that needed to be filled in the market.

By combining machine learning and his expertise in eye health, the mission of Digital Diagnostics is to provide an automated approach to detecting health risks, initially in the human eye. The basic idea is that with an automated system, more patients can potentially get quicker access to the diagnostics tests and results needed to avoid blindness.

Rainford sees the Digital Diagnostic approach as being both more scalable than requiring only human doctors and it can also be more cost effective as well.

“If you think about what’s required today to deliver the same thing that we’re delivering through this technology, you begin to think of a person going through med school, then more time at a residency or fellowship and further training,” Rainford said. 

Even after a human completes all the training to become qualified, the doctor could choose to work in a city center rather than a rural or underserved area. Rainford said that the goal with Digital Diagnostics is to allow for easier access to eye care diagnosis.

“We’re enabling or unlocking access to high quality-specialist level of care, at least from a diagnosis standpoint, and then we’re able to triage those patients that actually are losing their sight to the specialists that have spent all those years going to school,” he said.

How autonomous AI powers Digital Diagnostics

The Digital Diagnostics technology is not intended to just assist a clinician, it is actually intended to make a diagnosis, instead of a clinician.

Rainford noted the company’s FDA-approved system uses what is known as a fundus camera, which is an image-acquisition camera specialized for the human eye. The images from the camera are analyzed by Digital Diagnostics client software and its embedded AI.

Rainford emphasized that the AI is not a continuous learning model, but rather is based on an FDA-approved model.

“Our AI was approved by the FDA and now that algorithm is fixed until we go back to the FDA with something different,” Rainford said. “So there is not a continuous learning behind the scenes, we know what the algorithm is doing and everything is traceable.”

Looking forward, Digital Diagnostics has its sights set on disease detection beyond just the human eye. In 2020, Digital Diagnostics acquired privately-held 3Derm systems, which has expertise in dermatology.

“We’re working on the very same kind of technology for things like skin cancer and other skin diseases that, of course, are outside of the eye but the same thesis can hold true where we’re trying to democratize access to specialist-quality testing,” Rainford said.

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Author: Sean Michael Kerner
Source: Venturebeat

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