Subscribe to the feed

At Red Hat, we believe that open source has the power to unlock the world’s potential and is the best way to further innovation–especially when it comes to artificial intelligence (AI). AI has the power to transform the way we work and solve problems across industries, even in those that have yet to utilize AI to its fullest potential, like healthcare.

Currently, the use of AI in clinical settings is not common, but with solutions like Red Hat OpenShift AI, that could change. The challenge in adoption is partially due to a distrust among clinicians of proprietary AI models driven by a lack of transparency in many models’ design and data origin. Many proprietary AI models available to healthcare providers also lack the flexibility required by the user’s dynamic setting, such as being able to fine-tune a model to be specifically trained against health information.

The application of AI in specialties like maternal-fetal medicine has been met with several challenges, notably the sheer costs and skills required to bring AI workloads to bear, especially given the regulatory and compliance requirements that healthcare institutions must meet. Despite studies showing the impact one’s fetal health can have on an individual’s health as an adult, very few hospitals can establish AI-driven proof of concepts (PoCs) let alone produce AI pipelines due to resource constraints.

Red Hat has helped boost efficiency in a field where time is of the essence via the ChRIS Research Integration Service, a web-based medical image platform developed using Red Hat technologies on the Massachusetts Open Cloud (MOC). Now, AI running on a Red Hat OpenShift foundation can be used to aid physicians in faster diagnosis of their patients by reducing the time spent on analyzing diagnostic images. As an open source platform, Red Hat OpenShift AI can help healthcare providers bridge these gaps with rapid iteration and flexible deployment, keeping models relevant as other factors change thanks to the ability to continuously tune AI models built on the platform. Red Hat OpenShift AI can help clinicians analyze diagnostic images more efficiently–allowing them to identify the most relevant images among thousands taken of a patient, which is currently a manual and time-consuming task.

Incorporating open source AI into life-saving applications like this makes it possible to further democratize diagnostic data and AI models built on Red Hat OpenShift AI. This, in turn, lowers barriers to AI adoption by healthcare facilities with limited resources around the world and broadening the impact AI can have on the well-being of our population. With the power of open source, AI has the ability to improve the health and well-being of populations around the world.

About the author

Steven Huels is a Software Development and Implementation Executive with a demonstrated track record leading multi-discipline organizations to achieve strategic objectives. Huels is known for building teams and growing market share through creativity and thought leadership in evaluating, setting direction, and successfully executing in response to market and organizational demands. Some areas of his expertise include Artificial Intelligence / Machine Learning, SaaS/PaaS/Big Data, and System Development/Integration.

Read full bio

Browse by channel

automation icon


The latest on IT automation for tech, teams, and environments

AI icon

Artificial intelligence

Updates on the platforms that free customers to run AI workloads anywhere

open hybrid cloud icon

Open hybrid cloud

Explore how we build a more flexible future with hybrid cloud

security icon


The latest on how we reduce risks across environments and technologies

edge icon

Edge computing

Updates on the platforms that simplify operations at the edge

Infrastructure icon


The latest on the world’s leading enterprise Linux platform

application development icon


Inside our solutions to the toughest application challenges

Original series icon

Original shows

Entertaining stories from the makers and leaders in enterprise tech