5/12/2022 Ivan Sanchez for HCESC
Each year, the summit, hosted by the Health Data Analytics Initiative, aims to revise and inform about state-of-the-art knowledge in the fields of data driven health analytics. Even though this year's summit was only one day long, it served as a multi-health discipline melting point of research and discovery for clinical investigators and AI Data Scientists, giving them the opportunity to form research collaborations.
Written by Ivan Sanchez for HCESC
The University of Illinois and the Health Care Engineering Systems Center celebrated the 5th Annual Illinois Health Data Analytics Summit on April 4, 2022. Each year, the summit, hosted by the Health Data Analytics Initiative, aims to revise and inform about state-of-the-art knowledge in the fields of data driven health analytics. Attendees gain the knowledge needed to connect technical concepts with challenges. In-depth keynotes, networking opportunities, panel discussions, and breakout sessions are offered to support future collaborations.
This year’s summit agenda focused on strategies and technical concepts to overcome data scarcity, other challenges that undermine medical and clinical research occurring in rare diseases research, and clinical trials with small and non-diverse sample sizes. Presented were concepts such as Few-Shot Learning, Federated Learning, and AI based strategies that may potentially advance medical and clinical research for rare diseases and to improve health care for minorities.
The attendance at this year’s summit was the largest to date. This reflects the growing interest in health data analytics by the research community.
Featured at the summit this year were two keynote presentations: one by Eric Klee of the Mayo Clinic on ‘The Challenges of an N=1 Genetic Disease Paradigm in a Big Data World,’ and the second by James Rehg of Georgia Tech on ‘The Measurement and Modeling of Social Behavior in Infancy.’ Data science sessions and 14 talks with topics that ranged from data-efficient algorithms in healthcare, to ensuring security & privacy regarding small data sets, and rare disease deep phenotyping powered by data science were also garnered great interest from attendees.
Even though the summit was only one day long, it served as a multi-health discipline melting point of research and discovery for clinical investigators and AI Data Scientists, giving them the opportunity to form research collaborations. Such interdisciplinary collaborations advance fundamental medical research and care delivery utilizing actionable artificial intelligence and machine learning.
“We know of at least two collaborations that were formed at our summit, and this kind of ‘tangible’ outcome keeps us going,” said George Heintz, Director of the Health Data Analytics Initiative.
The Health Data Analytics Summit was initiated by the Grainger College of Engineering for the data scientists, and medical/clinical investigators here on campus, and for the investigators of our healthcare partners. To see some of the discussions and keynotes from the summit, you can find them here.
Summit Planning Committee: Computer Science, Veterinary Medicine, Electrical Computer Engineering, Gies College of Business, the School of Social Work, Interdisciplinary Health Science Institute, National Center for SuperComputing Applications, and the Grainger College of Engineering Dean’s Office of Research. The summit was also very proudly supported by our friends and clinical partners at OSF HealthCare, Carle Hospital and the Mayo Clinic.