Computer Sciencenpj Digital Medicine
Generation and evaluation of artificial mental health records for Natural Language Processing
J. Ive, N. Viani, et al.
Limited access to mental health records has stifled NLP innovations in clinical settings. Researchers, including Julia Ive and Natalia Viani from Imperial College London, unveil a promising method for generating artificial clinical documents, showing that such data can match original records for training NLP models while safeguarding sensitive information.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Medicine and Health
Natural language processing system for rapid detection and intervention of mental health crisis chat messages
A. Swaminathan, I. López, et al.
Medicine and Health
Natural language processing of multi-hospital electronic health records for public health surveillance of suicidality
R. Bey, A. Cohen, et al.
Medicine and Health
The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality
J. Torous, J. Linardon, et al.
Medicine and Health
Cohort design and natural language processing to reduce bias in electronic health records research
S. Khurshid, C. Reeder, et al.
