LPSGM: A Unified Flexible Large PSG Model for Sleep Staging and Mental Disorder Diagnosis.

ABSTRACT: We present the Large PSG Model (LPSGM), a unified and flexible framework for sleep staging and disease diagnosis using polysomnography (PSG) data. LPSGM is designed to address the challenges of cross-center generalization in sleep staging and to enable fine-tuning for downstream disease diagnosis tasks. LPSGM introduces a unified training framework for heterogeneous datasets and allows flexible channel input adjustments during inference. The model is first trained on 220,500 hours whole-night PSG from 16 public datasets, achieving robust sleep staging performance. It is then fine-tuned on target center data for various disease classification tasks, including narcolepsy diagnosis, anxiety and depression detection, and the classification of healthy versus depressed individuals. LPSGM outperf

SUBMITTER: Deng G 

PROVIDER: S-EPMC11661386 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature