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Response to: Significance and stability of deep learning-based identification of subtypes within major psychiatric disorders. Molecular Psychiatry (2022). (arXiv:2206.04934v1 [cs.LG])
June 13, 2022, 1:10 a.m. | Xizhe Zhang, Fei Wang, Weixiong Zhang
cs.LG updates on arXiv.org arxiv.org
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.
arxiv deep learning identification learning lg major significance
More from arxiv.org / cs.LG updates on arXiv.org
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