A multisource clinical deep learning model for early identification of mental disorders in first-visit psychiatric patients
IntroductionMental disorders often present with overlapping symptoms at the first psychiatric visit, making early identification difficult. This study included 5802 first-visit psychiatric patients and developed a TUCH-FT for multi-label classification of mental disorders using demographic information, clinical history, and item-level Symptom Checklist-90 data. Final diagnostic labels were…
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