The adoption of AI in clinical settings has increased exponentially over the past decade, but AI models still haven’t achieved the level of ubiquity that they could within the sector.

A few years ago, a group of Mayo Clinic researchers recognized this major problem. The health system was producing a huge amount of research on AI in clinical contexts, but it was still having a hard time actually deploying those AI models at scale.

That realization led to the creation of Lucem Health, a platform for clinical AI solution deployment. The North Carolina-based startup, which launched in 2021, closed a $7.7 million Series A funding round last week.

The financing round, which takes the company’s total funding to date to $13.7 million, included investments from Mayo Clinic, Mercy, Granger Management and Rally Ventures.

“Lucem is a Latin word that means dawn or light of day. The idea behind the formation of the company was that we are helping clinical AI innovation see the light of day,” said CEO Sean Cassidy in a recent interview.

The startup’s platform takes in the data required to fuel AI algorithms that give clinicians insights to improve patient care.

“We take in the data, and then we provide a mechanism to run virtually any kind of AI algorithm on our platform. We connect data to the AI, and then what pops out are predictions and insights. And then we have capabilities that allow us to surface that insight in the right place at the right time in the right context for the right stakeholder — so that it can actually be useful,” Cassidy explained.

A few weeks ago, the company released Lucem Health Reveal, which is meant to help providers deliver more proactive care. Using patient data, the suite of solutions identifies patients who might be at a higher risk of serious or chronic diseases, such colorectal cancer or diabetes.

Lucem sells its platform to health systems, as well as providers that have a smaller number of patients, such as single hospitals or multi-specialty physician practices.

“We can scale our solutions down so that they can operate on a relatively small number of patients. Now, there are some costs associated with deploying them, so you’re going to need some reasonable volume of patients, but it doesn’t have to be millions of patients. It can be thousands of patients that we can run these algorithms against, and they can surface a tremendous amount of potential value in terms of detecting diseases earlier,” Cassidy said.

There’s also another company that recently received an influx of capital for its platform to enable greater AI adoption in healthcare: Health Universe. Oncology Ventures CEO Ben Freeberg recently told MedCity News that this startup, which provides the underlying infrastructure to support the use of AI in healthcare settings, is one of the few startups his venture firm has bet on recently to improve the quality of cancer care.

Health Universe focuses on helping AI developers commercialize and scale AI models into the healthcare ecosystem, whereas Lucem’s focus is more about helping providers easily deploy these models throughout their enterprise. This focus sets Lucem apart, as does its team, Cassidy declared.

“Our team has come through the school of hard knocks in digital health and knows how to build stuff that meets provider organizations where they are,” he said.

Photo: metamorworks, Getty Images