Researchers have reported that the predictive abilities of a machine learning algorithm trained using best practices on a large clinical dataset did not generalize beyond the data that was used to train it. The algorithm was able to predict, to a degree, which individual patients would benefit from the medication when the patients were from the dataset the algorithm was trained on. But when it was supposed to predict who would benefit in clinical cohorts that were not part of the training, it performed no better than chance.