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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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Автори: Chengxi Zang, Yu Hou, Daoming Lyu, Jun Jin, Shane Sacco, Kun Chen, Robert Aseltine, Fei Wang
Формат: Artigo
Мова:Inglês
Опубліковано: Nature Publishing Group 2024-07-01
Серія:Translational Psychiatry
Онлайн доступ:https://doi.org/10.1038/s41398-024-03034-3
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