School of Social and Political Science

Research interests

 PhD project: Platformization in Diagnostic AI: Examination of Different Strategies for Scaling-up

The process of deploying AI in healthcare practice is slower than expected. The challenges of procurement, validation, integration, and post-surveillance were potentially insurmountable for a standalone AI. My project was launched at a particular juncture when suppliers, users and regulators simultaneously resort to an intermediary strategy — platform. It refers to a strategy to solve the challenges of diagnostic AI deployment as a community, meanwhile connecting external players and internals in the long term. I will reflect upon the new solution drawing on STS theories with a focus on qualitative research methods in order to understand how this new institutional and technological machinery is being created to allow various diagnostic AI tools to be sustainably exploited at scale.

I am supervised by: Prof. Robin Williams, Prof. Stuart Anderson, Dr. Michael Barany

Google Scholar: https://scholar.google.com/citations?user=_ECnkkgAAAAJ&hl=en&citsig=AM0yFClaHG_noY1eIHPPpd2bC8V0

Publications:
Williams, R., Anderson, S., Cresswell, K., Kannelønning, M. S., Mozzafar, H., & Yang, X. (2024). Domesticating AI in medical diagnosis. Technology in Society, 102469.

Yang, X., Gao, J., Liu, J. H., & Zhou, T. (2018). Height conditions salary expectations: Evidence from large-scale data in China. Physica A: Statistical Mechanics and its Applications, 501, 86-97.

Conference Presentations:

Yang, X. “How the different diagnostic AI get embedded into healthcare”. Conference 4S, 2023, Nov, Honolulu, US. 

Yang, X. “Beyond image: How Brain Legions are Automatically Recognised”. Conference EASST, 2022, July, Madrid, Spain.