Last week, I had the great privilege of delivering the keynote speech at University of Illinois Chicago
@thisisUIC Computational Research Symposium. The talk, titled "Building AI Infrastructure and Training Resources for a Learning Health System," addressed the urgent need to develop a multidisciplinary workforce skilled in collaborative AI in healthcare.
In this rapidly evolving field, it is crucial to foster synergy among diverse teams to leverage AI's full potential effectively. During my presentation, I shared our journey at
@NUFeinbergMed in creating a comprehensive suite of data tools, and educational resources aimed at equipping the next generation of professionals. Our initiatives include:
- Unlocking structured information from clinical notes for interoperable and self-service access.
- Crafting multi-modal AI/ML tools and tutorials to enhance capabilities in analyzing complex healthcare data.
- Cultivating environments (e.g., AI4H clinic, Northwestern Medicine Healthcare AI forum) where clinicians and AI scientists can collaborate and innovate together.
These efforts have not only led to dozens of highly cited publications but also supported successful acquisition and implementation of many federal grants. They've significantly empowered clinicians, scientists, and hospital administrators to integrate AI into their research and everyday practice, fostering closer collaborations and advancing our learning health system.
For those interested in deeper insights, our latest findings are detailed in our newly published paper in the Learning Health System journal. This is a Herculean team effort from all the authors and just the beginning, and I am excited about the future of AI in healthcare.
Let's continue to innovate and collaborate for a healthier tomorrow!
No Paywall:
onlinelibrary.wiley.com/doi/…
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