Yeung, Joshua Au

A framework to assess clinical safety and hallucination rates of LLMs for medical text summarisation

Asgari, E., Montaña-Brown, N., Dubois, M., Khalil, S., Balloch, J., Yeung, J. A., & Pimenta, D. (2025) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 423

AI chatbots not yet ready for clinical use

Yeung, J. A., Kraljevic, Z., Luintel, A., Balston, A., Idowu, E., Dobson, R. J., & Teo, J. T. (2023) · Frontiers in Digital Health

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 176

Foresight-a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study

Kraljevic, Z., Bean, D., Shek, A., Bendayan, R., Hemingway, H., Yeung, J. A., Deng, A., Balston, A., Ross, J., Idowu, E., et al. (2024) · The Lancet Digital Health

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 169

The Psychogenic Machine: Simulating AI Psychosis, Delusion Reinforcement and Harm Enablement in Large Language Models

Yeung, J. A., Dalmasso, J., Foschini, L., Dobson, R. J., & Kraljevic, Z. (2025) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 12

An Echo Chamber of One: Should AI Psychosis Be a Distinct Clinical Entity?

Yeung, J. A., Morrin, H., Ng, V., Kraljevic, Z., & Dobson, R. (2026) · arXiv

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 0