An unsupervised learning model for pattern recognition in routinely collected healthcare data
This study examines a large routinely collected healthcare database containing patient-level self-reported outcomes following knee replacement surgery. A model based on unsupervised machine learning methods, including k-means and hierarchical clustering, is proposed to detect patterns of pain experi...
| Главные авторы: | , , |
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| Формат: | Conference item |
| Опубликовано: |
Scitepress
2018
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