Health Intelligence for Future – Building AI-Infused Clinical Decision Support Systems
About This Video
What does the future of health intelligence look like? The idea of leveraging machine intelligence to improve clinical decision-making has fascinated healthcare and Artificial Intelligence (AI) researchers for decades. While all clinical AI models can offer valuable diagnostic or treatment suggestions, none is always correct. Therefore, it is critical to enable clinicians to use an effective AI-Infused Clinical Decision Support Tool (DST) to finalize their evidence-based decision-making processes.
In this workshop, I will mainly discuss the transformative impact of this futuristic clinical DST on the healthcare industry and how GPT-3 can assist in the development of this AI-Infused Clinical DST by handling qualitative and quantitative data.
In This Video
PhD Research Fellow, Cornell University
Yuexing Hao is a Ph.D. student in Human Behaviour Design at Cornell University. She holds two Computer Science degrees from Rutgers University (B.A.) and Tufts University (M.S). During her study, Yuexing won Meritorious Prize in the 2020 Interdisciplinary Contest in Modeling (ICM) and Graduate Student Research Competition Award at Tufts University. Yuexing also published several papers on CHI, Intelligent System Conference, HHAI, and Bioinformatics. Currently, her research focus is on Health Intelligence and Human-Computer Interaction.