“…However, there still exists a gap between these models and human interpretability, especially for clinicians who frequently seek discrete disease subtypes (Miotto et al, 2018). Thus, many recent efforts to discover the heterogeneous nature of brain diseases have investigated different clustering algorithms (Chand et al, 2020; Dong et al, 2016a, 2016b; Dwyer et al, 2018; Ezzati et al, 2020; Filipovych et al, 2012; Honnorat et al, 2019; Jeon et al, 2019; Jung et al, 2016; Lubeiro et al, 2016; Nettiksimmons et al, 2014; Ota et al, 2016; Pan et al, 2020; Park et al, 2017; Planchuelo-Gómez et al, 2020; Poulakis et al, 2020, 2020, 2018; Sugihara et al, 2016; Ten Kate et al, 2018; Varol et al, 2017; Young et al, 2018; Zhang et al, 2016). These methods can be divided into two categories depending on whether the clustering algorithm is unsupervised or semi-supervised b .…”