Accuracy and transportability of machine learning models for adolescent suicide prediction with longitudinal clinical records
Abstract Machine Learning models trained from real-world data have demonstrated promise in predicting suicide attempts in adolescents. However, their transportability, namely the performance of a model trained on one dataset and applied to different data, is largely unknown, hindering the clinical a...
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| Hauptverfasser: | , , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Publishing Group
2024-07-01
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| Schriftenreihe: | Translational Psychiatry |
| Online-Zugang: | https://doi.org/10.1038/s41398-024-03034-3 |
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