Recently, Winter and Hahn [1] commented on our work on identifying subtypes of major psychiatry disorders (MPDs) based on neurobiological features using machine learning [2]. They questioned the generalizability of our methods and the statistical significance, stability, and overfitting of the results, and proposed a pipeline for disease subtyping. We appreciate their earnest consideration of our work, however, we need to point out their misconceptions of basic machine-learning concepts and delineate some key issues involved.
翻译:最近,Winter和Hahn [1] 评论了我们利用机器学习,根据神经生物特征确定重大精神病亚型的工作,他们质疑我们的方法的可概括性以及统计意义、稳定性和结果的过度匹配,并提议为疾病分型提供管道,但我们赞赏他们认真审议我们的工作,但是,我们需要指出他们对基本机学概念的错误认识,并阐明所涉及的一些关键问题。