Dynamic Updating of Psychosis Prediction Models in Individuals at Ultra-High Risk of Psychosis
Dynamic updating of psychosis prediction models may help to mitigate decreases in performance over time. Therefore, existing psychosis prediction models need to be monitored for temporal biases to mitigate potentially harmful decisions.
Authors
- Ashleigh Lin (ORCID: https://orcid.org/0000-0002-4054-0242)
- Stephen James Wood (ORCID: https://orcid.org/0000-0003-4186-5919)
- Dominic Dwyer (ORCID: https://orcid.org/0000-0003-3949-5867)
- Scott Richard Clark (ORCID: https://orcid.org/0000-0003-1640-5611)
- Isabelle Scott (ORCID: https://orcid.org/0000-0001-8293-6125)
- Barnaby Nelson (ORCID: https://orcid.org/0000-0002-6263-2332)
- Patrick D. McGorry (ORCID: https://orcid.org/0000-0002-3789-6168)
- Josh Nguyen (ORCID: https://orcid.org/0000-0002-9106-0388)
- Simon Hartmann (ORCID: https://orcid.org/0000-0001-9689-0594)
- Alison Ruth Yung (ORCID: https://orcid.org/0000-0002-0401-9791)
- Cassandra M. J. Wannan (ORCID: https://orcid.org/0000-0003-1317-4635)
- Christel Maria Middeldorp (ORCID: https://orcid.org/0000-0002-6218-0428)
Institutions
- Deakin University (AU)
- The University of Melbourne (AU)
- The University of Western Australia (AU)
- Children’s Health Queensland Hospital and Health Service (AU)
- Orygen Youth Health (AU)
- Public Health Service of Amsterdam (NL)
- The University of Adelaide (AU)
Publication Details
- Journal
- Biological Psychiatry Cognitive Neuroscience and Neuroimaging
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1016/j.bpsc.2025.03.006
- Citations
- 6
- Primary Topic
- Schizophrenia research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 8.83