Machine-learning techniques are used in this BJPsych special issue on precision medicine in attempts to create statistical models that make clinically relevant predictions for individual patients. In this primer, we outline five key points that are helpful for a new reader to consider in order to engage with the field and evaluate the literature. These points include the consideration of why we are interested in new statistical approaches, how they may produce individualised predictions, what caveats need to be kept in-mind and why the interest and engagment of clinicians and clinical researchers is critical to successful model development and implementation. We hope that the following primer will provide shared understanding to encourage dialogue between clinical and methodological fields.

本期 BJPsych 关于精准医学的特刊中使用了机器学习技术，试图创建统计模型，为个体患者做出临床相关的预测。在这本入门书中，我们概述了五个关键点，有助于新读者考虑以参与该领域并评估文献。这些要点包括考虑我们为什么对新的统计方法感兴趣、它们如何产生个性化的预测、需要牢记哪些注意事项以及为什么临床医生和临床研究人员的兴趣和参与对于成功的模型开发和实施至关重要. 我们希望以下入门书将提供共同的理解，以鼓励临床和方法学领域之间的对话。