A self-driving car pioneer teamed up with a doctor to create a healthcare AI startup that just raised $16.5 million to upend radiology
- Nines Radiology is focused on using technology, including artificial intelligence, to help radiologists.
- Nines was cofounded by David Stavens, a self-driving car pioneer and Dr. Alexander Kagen, a New York City radiologist.
- The company has created a product that is supposed to help radiologists prioritize their time for patients most in need of treatment and diagnose them faster.
- The product, called the Emergent Neuro Suite, is now under FDA review.
- The startup just raised $16.5 million from investors including the venture firms Accel and 8VC.
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It was a nontraditional marriage of tech and medicine. But when Dr. Alexander Kagen and David Stavens first met, they believed their vision for healthcare could save lives.
In 2017, they founded Nines Radiology, a startup focused on advanced technology applications for radiologists - doctors who make diagnoses based on medical imaging. The startup just raised a series A funding round, taking in $16.5 million from investors including venture firms Accel and 8VC.
Part of the company is a teleradiology service, staffed by specialists from institutions like Mount Sinai Health System. Teleradiology allows radiologists to look at x-rays and other imaging remotely and provide diagnoses for patients.
The other part of the company works on artificial intelligence (AI) and machine learning (ML) applications. Nines created the Emergent Neuro Suite, a triage tool which is supposed to help radiologists prioritize their time for patients most in need of treatment. The goal is to improve patient and doctor experience with more efficient and accurate diagnoses, and the product is currently being reviewed by the Food and Drug Administration.
"The idea is to allow radiologists to get to the sickest patients first, which is the best we can do in terms of quality and safety," Kagen, the chief medical officer of Nines, told Business Insider.
Kagen overseas the radiology team in New York, while Stavens oversees the engineering team in San Francisco. The product is currently under FDA review.
Teleradiology is estimated to be an $11.5 billion industry by 2026, with the fastest area of growth coming from CT scans, according to a report by Grand View Research.
According to a Business Insider Intelligence report, the number of FDA-approved AI solutions for radiology is growing faster than other applications of AI in imaging. AI-generated healthcare savings could be more than $150 billion by 2025, as AI can improve outcomes and reduce treatment costs, according to the report.
How an AI expert and radiologist formed their partnership
In 2016, Stavens and Kagen met through a mutual friend and hit it off. Both saw the benefits of marrying AI and radiology to provide health benefits for patients and help radiologists manage their workload.
While each come from very different backgrounds, they saw the technological need in radiology.
Kagen, the site chair of radiology at Mount Sinai West and Mount Sinai St. Luke's hospitals in New York City, has been interested in AI for some time. In 2014, while doing research for Parkinson's disease he saw how a simple algorithm could accurately predict if someone had Parkinson's.
"I saw it as the future of medicine," Kagen said.
Stavens said Kagen understood the need for AI in radiology.
"He was one of the early adopters of the mindset," Stavens, the CEO of Nines, told Business Insider. "He wanted to be an agent of change and help design the technology."
Stavens brought to the table a wealth of knowledge of AI. He cofounded Stanford University's self-driving car team which was later acquired by Google and is now the foundation for Waymo. He then cofounded and was CEO of Udacity, which used AI to help build an online learning platform.
Stavens said he couldn't have predicted he'd be in the radiology or diagnostics space, but as he says, his career has taken unpredictable turns for a reason.
"The driving force of my career has been applying advanced technology to solve problems that affect humanity," Stavens said.
In healthcare, Stavens said data driven analysis is being used more to improve medical diagnosis. "I see the need for technology in healthcare. Its time has come."
Why radiology is ready for AI
Right now, radiologists must look at thousands of imaging scans for patients and make accurate diagnoses. The sheer volume of scans is becoming overwhelming for radiologists to analyze, Kagen said.
In order to help radiologists with the volume of data help patients see their physicians faster, Stavens and Kagen wanted to create a product that would be able to detect the sicker patients in the queue of scans. An alert would then be sent to the radiologist to evaluate the scan faster and help the patient.
"Maybe patient 10 in the queue is sicker than patient four," Dr. Kagen said. "It would be great if there was a way where we could define patient 10 and flag the radiologist."
For Kagen, an important aspect of Nines is that the radiologists at Mount Sinai can communicate with the engineers in Silicon Valley and tell the engineers specifically what technological improvements the product needs.
For the cofounders, giving radiologists technological input is vital for the engineers to create the strongest product.
"We'll implement this software with teleradiology services," Dr. Kagen said. "Radiologist can play an active and prominent role working with engineers, allowing them to be the best superdoc they can be."
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