- Unsupervised Machine Learning to Identify Depressive Subtypes
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Kung B, Chiang M, Perera G, Pritchard M, Stewart R
- KMID: 2532453
- Healthc Inform Res.
- 2022 Jul;28(3):256-266.
- doi: 10.4258/hir.2022.28.3.256
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... -
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