Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis
Abstract Background Clinical research and medical practice can be advanced through the prediction of an individual’s health state, trajectory, and responses to treatments. However, the majority of current clinical risk prediction models are based on regression approaches or machine learning algorith...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-12-01
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| Series: | BMC Medical Research Methodology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12874-019-0863-0 |