CASE STUDY anywhere a reality . With open-source , enabling AIfuelled innovation across hybrid IT environments that can lead to faster clinical breakthroughs and better patient outcomes is a reality .
Chris Wright , CTO and Senior Vice President , Global Engineering , Red Hat , said : “ Boston Children ’ s Hospital exemplifies the positive impact Artificial Intelligence can have in the healthcare field and how it fuels innovation beyond traditional enterprise IT . Red Hat is proud to collaborate with Boston Children ’ s Hospital by providing the technology foundation for efforts to make a difference in the health of future generations .”
Ellen Grant , M . D ., Pediatric Neuroradiologist , Director of the Fetal Neonatal Neuroimaging and Developmental Science and Director of Research at the Maternal Fetal Care Center , said : “ I acknowledge and appreciate Red Hat ' s collaborative approach to piloting open-source AI tools for maternal fetal medicine with my team at Boston Children ' s Hospital .” p
The influence of open source and AI in healthcare
Steven Huels , Vice President & General Manager of Artificial Intelligence Business , Product and Strategy , Red Hat , on the potential for AI in clinical settings .
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 .
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