Relapse prediction using wearable data through convolutional autoencoders and clustering for patients with psychotic disorders
Abstract Relapse of psychotic disorders occurs commonly even after appropriate treatment. Digital phenotyping becomes essential to achieve remote monitoring for mental conditions. We applied a personalized approach using neural-network-based anomaly detection and clustering to predict relapse for pa...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-03856-1 |
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