“Take10: Towards a Novel Ecosystem for Transparent Integration of AI in Clinical Flow” is a presentation by Dr. Yelena Yesha and Dr. Pierre-François d’Haese on the basis of a novel ecosystem developed between the West Virginia University Rockefeller Neuroscience Institute and the University of Miami Institute for Data Science and Computing (IDSC).
This Consortium brings together multidisciplinary expertise in large radiology systems, medical imaging analytics, large clinical data management, ML/AI, radiomics, real-world evidence collection, and regulatory access to extensive clinical flow and data.
Monday, November 29, 11:00 AM ET via Zoom for Government
Artificial intelligence (AI)- and machine learning (ML)-based technologies have the potential to transform healthcare by deriving new and essential insights from the vast amount of data generated during the delivery of healthcare every day. Example high-value applications include earlier disease detection, more accurate diagnosis, identification of new observations or patterns on human physiology, and development of personalized diagnostics and therapeutics.
One of the most significant benefits of AI/ML in software resides in its ability to learn from real-world use and experience and its capability to improve its performance. The ability for AI/ML software to learn from real-world feedback (training) and improve its performance (adaptation) makes these technologies uniquely situated among software as a medical device (SaMD) and a rapidly expanding area of research and development.
While the FDA has made significant strides in developing appropriately tailored policies for SaMD to ensure the safe and effective technologies reach users, we believe that the next paradigm for device regulation needs to be ready for adaptive AI/ML technologies, which have the potential to adapt and optimize device performance in real-time to improve healthcare for patients continuously. Such change requires an approach based on a new technological ecosystem allowing for continuous testing and following of AI-based devices that facilitates a rapid product improvement cycle and allows these devices to improve continually while providing adequate safeguards.
The framework is based on three pillars:
- Seamless access of de-identified clinical data from radiology and medical records allowing for preliminary training of novel analytics models
- Low footprint compliant integration of AI models in the radiological clinical flow
- Gathering of information and monitoring of performances in conjunction with radiologists and clinical professionals.
Drs. Yesha and d’Haese will conclude with the presentation of opportunities of such systems to support continuous and AI-based regulatory frameworks.
About Dr. Yelena Yesha | UM IDSC
At the University of Miami, Dr. Yelena Yesha is the Knight Foundation Endowed Chair of Data Science and AI at the Institute for Data Science and Computing (IDSC). At IDSC, Dr. Yesha is also the Innovation Officer and Head of International Relations. In this role, Dr. Yesha assists faculty in engaging government and industrial partners to collaborate with the University and consults with faculty on developing research ideas into innovations.
Dr. Yesha was the Founding Director of the National Science Foundation Center for Accelerated Real Time Analytics (CARTA), an NSF-funded Industry/University Cooperative Research Center (I/UCRC) that aims to develop long-term partnerships among industry, academia, and government. CARTA partners with Rutgers University New Brunswick, North Carolina State University, the University of Maryland Baltimore County (UMBC), Tel Aviv University, and the University of Miami.
Dr. Yesha received her B.Sc. degrees in Computer Science and in Applied Mathematics from York University, Toronto, Canada, and her M.Sc. degree and Ph.D. degree in Computer Science from The Ohio State University She has published 11 books as author or editor, and more than 200 papers in prestigious refereed journals and refereed conference proceedings, and she has been awarded external funding in a total amount exceeding 45 million dollars. She is currently working with leading industrial companies and government agencies on new innovative technology in the areas of blockchains, cybersecurity, and big data analytics with applications to electronic commerce, climate change, and digital healthcare. Dr. Yesha is a fellow of the IBM Centre for Advanced Studies.
About Dr. Pierre-François d’Haese | WVU RNI
Dr. d’Haese is a serial entrepreneur and faculty at the intersection of data analytics and medicine. Most recently, Dr. d’Haese serves as the CEO of Neurotargeting and as the Director of Digital Health and Analytics at the Rockefeller Neuroscience Institute (RNI), an institution focused on the study of human memory and memory diseases. Dr. d’Haese defined the Institute’s digital health vision and analytics, leading a team of multidisciplinary engineers and scientists to build the next generation of AI-driven clinical diagnosis and intervention tools. Dr. d’Haese is an Associate Professor in NeuroRadiology and Computer Science and Elec. Engineering.
Prior to the RNI, Dr. d’Haese started and advised numerous MedTech startups while pursuing an academic path in parallel. Among other projects, Dr. d’Haese built cloud-based medical imaging analytics pipelines to foster discoveries for neurodegenerative disease across academic centers, published on neurodegenerative pathologies such as Parkinson’s or focused ultrasound brain-blood-barrier opening for Alzheimer’s, and developed novel neurosurgical software systems for computer-assisted intervention for DBS and Epilepsy.
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