Accelerate the use of AI in healthcare with training tools from Redbrick AI

Artificial intelligence technology represents a huge opportunity for diagnostics in medicine: with the right training, AI systems can quickly process large numbers of scans and images, and pinpoint problems with pinpoint accuracy. outstanding. But there is a problem - training AI is time consuming and laborious. Enter RedBrick AI, an American start-up, which today announces a fundraising of 4.6 million dollars to accelerate its scale; his tools and technologies can make a huge difference, he believes.

“AI is remarkably good at making diagnoses; by using AI, you can automate 40% of breast cancer diagnoses, for example,” says CEO and co-founder of RedBrick AI, Shivam Sharma "However, there is a real challenge: these systems are not simple to build, and healthcare in particular poses unique challenges."

Put simply, to train an AI system, researchers need to show it as much data as possible: images and scans if your goal is to train it to read them. Each scan should be annotated to tell the system what it represents - an image of a cancer-free patient, perhaps, or an image including a potentially troublesome area that needs to be investigated - so the AI ​​can know what what she is looking for.

The problem here, says Sharma, is that no one has developed tools to help clinicians annotate images quickly and easily so that large amounts of data can be fed into the AI ​​system quickly. "Due to the complexity, size, and unique nature of medical images, clinicians must rely on traditional and difficult-to-use clinical tools to perform annotations," he explains.

In this regard, Redbrick AI's unique selling point is that it has developed a set of specialized annotation tools designed specifically for the healthcare profession. She estimates that by using her tools, clinicians and programmers can reduce the time it takes to train an AI system by up to 60%.

This represents a significant breakthrough, opening up the possibility of accelerating the application of AI in healthcare. The medical profession is very open to such applications. In 2021 alone, the U.S. Food and Drug Administration approved 115 AI algorithms for use in medical environments, an 83% increase from 2018, but much more can be done and faster.

Redbrick AI believes it can improve existing technology in several important ways. First, its tools are tailor-made for the medical sector, rather than relying on more generic techniques that don't always reflect the nuances and specialties of healthcare. In addition, the tools are quickly accessible via its platform and can be used without any prior training. Also, the platform includes a number of automation facilities, which can manage and speed up workflows.

It's a value proposition that is rapidly gaining momentum in the healthcare industry, with customers from the US, Europe and Asia signing up within the first year of operation of the company. Redbrick AI offers its tools through a software-as-a-service model, with customers paying monthly subscriptions, based on their number of users, to access the platform.

“With the rapid growth of AI in clinical environments, researchers need excellent tools to create high-quality datasets and models at scale,” adds Sharma. "Our customers are at the forefront of this growth, pioneering everything from surgical robots to automated cancer detection."

Today's fundraiser should help Redbrick AI reach even more of these customers over the next 12 months. Sharma plans to deploy some of the funds raised to further develop the company's tools. It has also earmarked funds for its go-to-market strategy, in which Sharma plans to work with a larger number of corporate clients (large medical research and technology companies) as well as smaller teams of health specialists.

The $4.6 million round is led by Surge, the large-scale development program managed by Sequoia Capital India, with participation from Y Combinator and several business angels.

Sharma and co-founder Derek Lukacs are excited about the opportunity to scale the business faster. “In this space, everything starts and ends with the hospital,” Sharma explains. "It's the source of the raw data, but it's also where our technology will have the most impact, improving patient outcomes."