Israeli startup, Aidoc, a provider of artificial intelligence (AI) solutions for radiologists, has raised $27 million in a Series B financing that was led by Australian venture capital firm Square Peg Capital.
In a statement, Aidoc said the latest financing brings total investment to $40 million, with the money expected to be used to grow Aidoc’s technology and go-to-market team to support the high market demand for its products.
Aidoc co-founder and Chief Executive Officer, Elad Walach, said there was mounting evidence that the firm was demonstrating real value to patients.
“We feel a responsibility to get this technology into as many hospitals as possible, as soon as possible. Our aim is to reach 500 hospitals in the next two years and we’re proud to partner with Square Peg to support this growth,” Walach said in a statement.
In a blogpost explaining what the Series B financing round meant, Walach said the funding would catapult the company into a higher league, where, in addition to the development of new technologies and products, the startup would be able to scale up the deployment of its solution.
Dan Krasnostein, a partner at Square Peg Capital, described Aidoc as the most mature company for AI for radiology and said he believed that, with their partnership, the medical imaging startup would accelerate to triple-digit growth.
How Aidoc’s solutions work
The startup, which was founded in 2016, provides imaging solutions for radiologists to enhance their diagnosis by flagging acute anomalies in real-time. Aidoc, whose solutions are used at more than 100 medical centers, announced that it had recently analyzed a CT scan of its 1 millionth patient in real time, “the largest number of images analyzed by an AI tool and a landmark in the radiology AI ecosystem.”
Aidoc said its U.S. Food and Drug Administration or FDA-cleared and CE-marked solutions support and enhance the impact of radiologist diagnostic power, helping them expedite patient treatment and improve quality of care. Aidoc’s solution helps speedily detect any critical injuries such as spine fractures and brain hemorrhages.
“Radiologists benefit from deep learning technology that is ‘Always-on’, running behind the scenes and freeing them to focus on the diagnosis. Aidoc’s solution flags the most critical, urgent cases where a faster diagnosis and treatment can be a matter of life and death,” the startup continued.
Furthermore, it said its results are clinically proven and independently monitored. Walach said they were working with the American College of Radiology DSI to continuously monitor the “performance of our solutions that are already active within hospitals across the US. Providing public visibility on the real-life clinical impact of AI across diverse settings is crucial for the continued adoption of these technologies in medical practice.”
What makes Aidoc’s AI system an interesting proposition is that medical centers using the system do not need additional hardware to run the solution because integration is simple and does not need significant IT time. Most of the setup and maintenance is performed remotely, the startup said. In our list of best AI startups in healthcare, we pointed out that Aidoc’s solution to assist workflow optimizations and increase the number of correct and high-quality scans was likely to see demand for this AI-enabled technology rise.
The VentureBeat website explained that Aidoc’s AI-powered diagnostics tool set runs continuously in an on-premises virtual machine and ingests scans from picture archiving and communication and radiological information systems. “It deidentifies these and sends them onto Aidoc’s cloud, where algorithms identify and highlight abnormalities before returning the images to radiology workstations for reidentification,” the website reported.
Walach initially said that they thought their solution would be used to solely to affect workflow, but the company was now striving “to forge a robust work tool essential in supporting the daily workflow while improving quality of care.”
He said the startup wants AI to become a standard of care, there was need to accumulate a compelling body of evidence proving the clinical value of the AI systems.
“Today our systems process, annually, over a million cases in tens of hospitals. We need to be in thousands of hospitals running tens of millions of cases and saving the lives of thousands of people all over the world. Having this new funding at our disposal will give us the opportunity to produce a large volume of clinical outcomes, based on a wide install base. This, in turn, will pave the way towards making our AI solution into an integral part of the standard of care,” Walach said.
Aidoc is now working on releasing an oncology line of products, while it is also working on an extension of its X-ray suite for time-sensitive conditions. The startup has worked with the American College of Radiology Data Science Institute to come up with an industry-first AI validation process.