Unsupervised Machine Learning to Identify Depressive Subtypes
Objectives This study evaluated an unsupervised machine learning method, latent Dirichlet allocation (LDA), as a method for identifying subtypes of depression within symptom data. Methods Data from 18,314 depressed patients were used to create LDA models. The outcomes included future emergency prese...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The Korean Society of Medical Informatics
2022-07-01
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| Series: | Healthcare Informatics Research |
| Subjects: | |
| Online Access: | http://www.e-hir.org/upload/pdf/hir-2022-28-3-256.pdf |