Abstract
• Machine learning models predict risk for adverse events and likelihood of dropout. • Machine learning models predict disease progression risk and response to treatment. • Predictive models can be of great use in all stages of clinical trials. • Training data sets have to be diverse to maximize generalizability. • It is key to ensure patient safety and ethical use of the models.
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