Making a big impact with small datasets using machine-learning approaches

As comprehensive electronic medical records increasingly capture more data points from large-scale clinical cohorts, machine-learning approaches have been applied to identify patterns that would otherwise be challenging to ascertain with traditional statistical methods. Although we often think of machine learning for analysis of large, complex datasets, in The Lancet Rheumatology, George Robinson and colleagues1 successfully applied machine-learning algorithms to derive information from a small dataset in a rare disease.