Toward Gold Standards in Data Creation – AI Strategies to Address Data Accessibility Challenges in Biomedical Research
September 18, 2024 | 2:00 p.m. – 4:00 p.m. ET
Speakers:
- Özlem Uzuner, PhD, George Mason University
- C. Karen Liu, PhD, Stanford University
- Lee Cooper, PhD, Northwestern University
Join the National Library of Medicine (NLM) for an insightful and transformative webinar that delves into the intersection of the work of three groundbreaking, NLM-funded researchers, each harnessing the power of artificial intelligence and machine learning to overcome significant challenges in data accessibility. Whether it's through the extraction of information from electronic health record narratives, predicting treatment outcomes from biomechanics data, or interpreting medical images, through their work, each has developed innovative strategies to minimize the need for expert intervention in the data preparation process. By providing high-quality, de-identified, annotated, and labeled datasets has resulted in shared resources of great value to the research community that can serve as benchmarks to develop, test, and improve computational methods.
This webinar is a unique opportunity for data scientists, researchers, technologists, and those curious about NLM-funded research to explore collaborative strategies for creating high-quality datasets, reducing expert burden through using innovative data processing techniques, and fostering community engagement and collaboration. It shares the latest developments in these areas and stimulates discussions on how shared methodologies can be applied across domains to expand data availability for health research. Participants will gain a deeper understanding of the role of community-driven efforts in overcoming data challenges and the importance of collaboration in achieving breakthroughs in health research.
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