Fully Interpretable and Adjustable Model for Depression Diagnosis: A Qualitative Approach
Recent advances in machine learning (ML) have enabled AI applications in mental disorder diagnosis, but many methods remain black-box or rely on post-hoc explanations which are not straightforward or actionable for mental health practitioners. Meanwhile, interpretable methods, such as k-nearest nei...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2025-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Subjects: | |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/138733 |
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