When it comes to video-based data, advances in computer vision have given a huge boost to the research world, making the process of analyzing and extracting insights from moving images something that is scalable beyond the limits of a small team of people.
A startup called theater maker has applied this concept to the world of healthcare: it uses AI to “read” videos captured during surgery, to look for best practices, but also to help identify key moments when surgery has taken the wrong turn. Today, it is announcing $24 million in funding — a sign of how both the medical world is adapting and adopting advances in AI to improve its own work; and how investors are committed to betting on the opportunities ahead.
The funding is a significant expansion of Theator’s Series A of $15.5 million from February 2021, bringing the total for the round to $39.5 million and a total of $42.5 million.
As with the previous tranche, Insight Partners led this latest investment. Past backers Blumberg Capital, Mayo Clinic, NFX, StageOne Ventures, iAngels and former Netflix Chief Product Officer Neil Hunt also participated, along with new backers iCON and Ariel Cohen, CEO and co-founder of TripActions.
The valuation will not be disclosed, but the Serie A is noteworthy for another reason: bringing in a major strategic investor, in the form of the Mayo Clinic, which partners with Theator – based in Palo Alto with operations also in Israel – using its video analytics tools. Other partners include the Canadian Association of General Surgeons and others not yet announced. In total, Theator’s library has now accumulated 30,000 hours of anonymized video, with nearly 1 billion frames analyzed.
The market opportunity that Theator is tackling is this: In the world of surgery, a huge amount of video is already being created, particularly through the camera probes used in non-invasive procedures.
The main purpose of most of this video is, of course, for surgeons to be able to monitor what they are doing in real time. But Theator’s premise is that — tapped into effectively — this video could be an invaluable resource for those physicians, the healthcare facilities where they work, and potentially the areas in which they work (i.e., the wider network of other physicians working in the same fields as them), if it could be examined and compared with similar procedures performed elsewhere, and then compared with the results.
That may sound like an insurmountable task on a human level. There is too much video and the concept of parsing even part of it sounds too time consuming to execute. All this also means something else: in fact, the best results so far have stayed with those who do all the best work.
Or, as Dr. Tamir Wolf, the CEO and co-founder of Theator noted (leaning on an age-old saying), “Too often where you live determines whether you live.”
“There’s no real understanding of ground truths these days,” he continued, despite tens of millions of hours of video being created through visual guidance for various procedures. “None of that video is captured, stored, or analyzed. You lose the understanding of what goes on in the operating room, and the best practices. Being able to identify what best practices look like and then share them is what we want to do.”
And that’s where AI comes into the picture.
Wolf describes Theator’s platform as “surgical intelligence.” It takes many hours of footage and can identify key moments in any procedure in real time.
So during a six-hour pancreatic surgery, the system uses machine learning and computer vision to structure the raw images, compare that video with other videos of the same procedures, and then match what happens in the videos with results from previous procedures to meet the requirements of to hone in on the key features of “good outcome”, and where things have diverged.
The data is then shared with individual doctors, teams, their institutions and so on to create a better understanding for existing patients (to better manage aftercare) and for future procedures.
Many people tend to focus on the aftercare and the complications that can arise there after what is otherwise considered a “successful” procedure, but Dr. was not enough data and insight into the operation itself.
Wolf notes that some hospitals have worse outcomes than others for what are also identified as “successful” surgeries, because there were no real-time complications during the actual procedures.
Why is that the case? “We don’t know,” he said simply.
Wolf’s creation of Theator actually grew out of that question, which he asked himself as a physician, as well as a friend and relative of patients.
In particular, he recalled how both his wife and a friend/colleague happened to have the same surgery at the same time, but in different hospitals. Both went technically well, but one had a much greater long-term after-effect than the other. Trying to get to the bottom of why that turned out the way it did is what partially motivated what his startup is pursuing.
“Theator’s technology has proven to be the critical next step in surgical advancement,” Brad Fiedler, VP at Insight Partners, said in a statement. “Integrating AI and computer vision into the operating room improves surgical care and changes surgery for the better. We are excited to double our investment, especially as Theator’s expertise in AI and computer vision is now improving patient outcomes with an increasing number of commercial partners.”
To date, Theator has negotiated its deals with health care providers – that is, hospitals and clinics where procedures are performed – although you can imagine a scenario where insurance companies, individual doctors, and perhaps even patients want to access this kind of data to understand more about what’s going on, and perhaps more importantly – a bit like dashcams – to capture what’s going on in case something goes wrong.
This isn’t something Theator is pursuing right now, but it’s an obvious opportunity.
Likewise, there is a whole world of procedures that the startup is not currently addressing. Wolf described minimally invasive procedures as “low-hanging fruit” in this regard, as these surgeries already use cameras and capture video. Over time, there are a number of other, even more complicated, procedures that you can imagine could benefit from similar treatment.
At the same time, the market is still developing. Not everyone wants this kind of research and doesn’t believe it can provide an accurate picture of the full range of conditions associated with a single surgery or treatment of one person over another. It focuses, as it were, only on the aspects that the camera can capture.
And you could argue that once the parameters are put in for what’s “right”, it becomes more difficult and less likely for surgeons to take calculated risks that could lead to better outcomes than anything else becomes “default” based on the AI. training. It’s basically the same problem you get with other uses of AI when it essentially paints itself into a logical angle that clearly makes no sense to the human brain and our real reason, and is in fact no longer “intelligent” but the opposite .
However, that doesn’t detract from what Theator’s technology can do. It’s just a reminder that, as with all AI, there’s no doubt a lot more needs to be codified about using that intelligence in context.
In the meantime, “We are slowly seeing a shift in the minds of surgeons and others in this ecosystem that more transparency is needed,” Wolf said. “The switch to competency-based insights is part of that.” As a result, this technology may not only be applied to operations and best practices for everyone, but also for training. “Video will be at the heart of how surgeons are assessed to see if they can get out of their residency and practice in full.”