On March 8th, DLSPH faculty Dr. Laura Rosella and Dr. Hailey Banack co-chaired the Society for Epidemiologic Research (SER) 2024 Mid-Year Meeting in Toronto. The mission of SER is to keep epidemiologists at the forefront of scientific developments. The theme of the mid-year meeting was Innovative Data Science Applications in Epidemiology, attracting 150 attendees and over 60 virtual participants. Many also attended the evening social on Thursday March 7th.
We had an exciting program with two expert international keynote speakers, provoking panel discussions, and research talks about the application of new data and novel methods. Professor Magdalena Cerda from the Department of Population Health at NYU Grossman School of Medicine, who discussed emerging data science methods in precision public health to inform the response to the US opioid crisis, as well as leveraging large language models to automate coding of municipal laws. Dr. Irene Y. Chen from UC Berkeley and UCSF’s Computational Precision Health Program discussed AI and health disparities and outlined critical considerations to reduce bias for ethical AI in medicine. A panel of Canadian experts discussed data science at the intersection of public health and academia, noting that the rapid availability of big data renews the focus on data governance with increasing need for community engagement and transparency on how data are used.
The meeting highlighted the latest advances in data science as they relate to the field of epidemiology. Research talks included the use of data from wearables, social media, sound data, and synthetic data for epidemiological insights. Applications of artificial intelligence (AI) and machine learning were discussed in the context of public health surveillance, cancer AI, predictive epidemiology, and target trial emulation in nutrition. Dr. Laura Rosella and Dr. Jaky Kueper co-moderated the final session with a stellar panel and polling the audience to discuss the role of advanced data science and AI in modern epidemiology. It’s complicated: AI is rapidly evolving which provides a range of opportunities and challenges for the field of epidemiology.
SER members can login to listen to the recordings here.