Predicting transition to psychiatric disorders in clinical high-risk for psychosis subjects using machine learning and facial features.
- DOI
- 10.1016/j.schres.2026.06.001
- Published
- 2026 Sep
- Container
- Schizophrenia research
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.schres.2026.06.001,
title = {Predicting transition to psychiatric disorders in clinical high-risk for psychosis subjects using machine learning and facial features.},
author = {Loch AA and Queluz FH and Waurzenczak B and Gondim JM and Argolo FC and Lopes-Rocha AC and van de Bilt MT and de Jesus LP and Jafet AF and Gattaz WF and Cecchi GA and Corcoran CM and Ara A},
year = {2026},
journal = {Schizophrenia research},
doi = {10.1016/j.schres.2026.06.001},
url = {https://doi.org/10.1016/j.schres.2026.06.001}
}RIS
TY - JOUR TI - Predicting transition to psychiatric disorders in clinical high-risk for psychosis subjects using machine learning and facial features. AU - Loch AA AU - Queluz FH AU - Waurzenczak B AU - Gondim JM AU - Argolo FC AU - Lopes-Rocha AC AU - van de Bilt MT AU - de Jesus LP AU - Jafet AF AU - Gattaz WF AU - Cecchi GA AU - Corcoran CM AU - Ara A PY - 2026 JO - Schizophrenia research DO - 10.1016/j.schres.2026.06.001 UR - https://doi.org/10.1016/j.schres.2026.06.001 ER -
APA
AA, L., FH, Q., B, W., JM, G., FC, A., AC, L., MT, V. D. B., LP, D. J., AF, J., WF, G., GA, C., CM, C., & A, A. (2026). Predicting transition to psychiatric disorders in clinical high-risk for psychosis subjects using machine learning and facial features.. Schizophrenia research. https://doi.org/10.1016/j.schres.2026.06.001
Source records
- pubmed · retrieved 2026-09-26T22:41:37.703Z