A new bet on early heart failure detection and why women’s health is at the center.
Updated
January 8, 2026 6:28 PM
A doctor holding an artificial heart model. PHOTO: ADOBE STOCK
Heart disease does not always announce itself clearly, especially in women. Many of the symptoms are ordinary, including fatigue, shortness of breath and swelling. These signs are frequently dismissed or explained away. As a result, many women are diagnosed late, when treatment options are narrower and outcomes are worse. That diagnostic gap is the context behind a recent investment involving Ultromics and the American Heart Association’s Go Red for Women Venture Fund.
Ultromics is a health technology company that uses artificial intelligence to help doctors spot early signs of heart failure from routine heart scans. It has received a strategic investment from the American Heart Association’s Go Red for Women Venture Fund.
The focus of the investment is a long-standing blind spot in cardiac care. Heart failure with preserved ejection fraction, or HFpEF, affects millions of people worldwide, with women disproportionately impacted. It is one of the most common forms of heart failure, yet also one of the hardest to diagnose. Studies even show women are twice as likely as men to develop the condition and around 64% of cases go undiagnosed in routine clinical practice.
Ultromics works with a tool most patients already experience during heart care: the echocardiogram. There is no new scan and no added burden for patients. Its software analyzes standard heart ultrasound images and looks for subtle patterns that point to early heart failure. The goal is clarity. Give clinicians better signals earlier, before the disease advances.
“Heart failure with preserved ejection fraction is one of the most complex and overlooked diseases in cardiology. For too long, clinicians have been expected to diagnose it using tools that weren't built to detect it and as a result, many patients are identified too late,” said Ross Upton, PhD, CEO and Founder of Ultromics. “By augmenting physicians' decision making with EchoGo, we can help them recognize disease at an earlier stage and treat it more effectively.”
The stakes are high. Research suggests women are twice as likely as men to develop the condition and that a majority of cases are missed in routine clinical practice. That delay matters. New therapies can reduce hospitalizations and improve survival, but only if patients are diagnosed in time.
This is why early detection has become a priority for mission-driven investors. “Closing the diagnostic gap by recognizing disease before irreversible damage occurs is critical to improving health for women—and everyone,” said Tracy Warren, Senior Managing Director, Go Red for Women Venture Fund. “We are gratified to see technologies, such as this one, that are accepted by leading institutions as advances in the field of cardiovascular diagnostics. That's the kind of progress our fund was created to accelerate.”
Ultromics’ platform is already cleared by regulators for clinical use and is being deployed in hospitals across the US and UK. The company says its technology has analyzed hundreds of thousands of heart scans, helping clinicians reach clearer conclusions when traditional methods fall short.
Taken together, the investment reflects a broader shift in healthcare. Attention is shifting earlier—toward detection instead of reaction. Toward tools that fit into existing care rather than complicate it. In this case, the funding is not about introducing something new into the system. It is about seeing what has long been missed—and doing so in time.
Keep Reading
The focus is no longer just AI-generated worlds, but how those worlds become structured digital products
Updated
February 20, 2026 6:50 PM
The inside of a pair of HTC VR goggles. PHOTO: UNSPLASH
As AI tools improve, creating 3D content is becoming faster and easier. However, building that content into interactive experiences still requires time, structure and technical work. That difference between generation and execution is where HTC VIVERSE and World Labs are focusing their new collaboration.
HTC VIVERSE is a 3D content platform developed by HTC. It provides creators with tools to build, refine and publish interactive virtual environments. Meanwhile, World Labs is an AI startup founded by researcher Fei-Fei Li and a team of machine learning specialists. The company recently introduced Marble, a tool that generates full 3D environments from simple text, image or video prompts.
While Marble can quickly create a digital world, that world on its own is not yet a finished experience. It still needs structure, navigation and interaction. This is where VIVERSE fits in. By combining Marble’s world generation with VIVERSE’s building tools, creators can move from an AI-generated scene to a usable, interactive product.
In practice, the workflow works in two steps. First, Marble produces the base 3D environment. Then, creators bring that environment into VIVERSE, where they add game mechanics, scenes and interactive elements. In this model, AI handles the early visual creation, while the human creator defines how users explore and interact with the world.
To demonstrate this process, the companies developed three example projects. Whiskerhill turns a Marble-generated world into a simple quest-based experience. Whiskerport connects multiple AI-generated scenes into a multi-level environment that users navigate through portals. Clockwork Conspiracy, built by VIVERSE, uses Marble’s generation system to create a more structured, multi-scene game. These projects are not just demos. They serve as proof that AI-generated worlds can evolve beyond static visuals and become interactive environments.
This matters because generative AI is often judged by how quickly it produces content. However, speed alone does not create usable products. Digital experiences still require sequencing, design decisions and user interaction. As a result, the real challenge is not generation, but integration — connecting AI output to tools that make it functional.
Seen in this context, the collaboration is less about a single product and more about workflow. VIVERSE provides a system that allows AI-generated environments to be edited and structured. World Labs provides the engine that creates those environments in the first place. Together, they are testing whether AI can fit directly into a full production pipeline rather than remain a standalone tool.
Ultimately, the collaboration reflects a broader change in creative technology. AI is no longer only producing isolated assets. It is beginning to plug into the larger process of building complete experiences. The key question is no longer how quickly a world can be generated, but how easily that world can be turned into something people can actually use and explore.