NIH Developer Seminar: PennyLane, GPUs, and QML,QiML PDF + Discussion 11/30/23.
NIH's Office of Data Science Strategy Initiatives is catalyzing new opportunities in AI through the availability of FAIR and complete AI-ready data. With the goal of increasing widespread AI adoption, the nation's medical research agency aims to utilize important discoveries that improve health and save lives. NIH currently uses AI/ML in 27 of their institutes and centers, which includes the Office of the Director's 'Smart and Connected Health' initiative. (Slides 01, 02)
NIH is also engaged in quantum information science research through the National Quantum Initiative to ensure researchers benefit from new technologies; and is also collaborating with the Department of Energy’s Advanced Scientific Computing Research Office to explore opportunities at the intersection of quantum computing, biomedical research, and data science. (Slide 19)
Adoption of advanced physics based machine learning approaches using classical data generating and classical data processing systems has recently become a greater priority to many leading organizations. (Slide 04) With a Python based notebook, a quantum machine learning library, and classical hardware - further benefiting from the effects of quantum algorithms for medical dataset analysis remains a key area of research. (Slide 05)
With that being said, there are now many resources available to Healthcare developers for further QML/QiML implementation. (Slide 17) Next steps include increasing the number of Human-QiML Team interactions, additional testing for efficacy, and further implementing real world data in a community setting while forming prospective standards.