The field received significant interest in the previous decade, mainly due to advances in automated machine learning (ML) and deep learning (DL). They learn useful patterns from a large amount of data and keep the acquired knowledge as model structures and parameters that can be further applied to make predictions by interpreting unseen data [1]. These models are either a set of elements or features that contribute when making decisions (in ML) or are organized into several layers of abstraction (such as neural networks) for general and specific interpretation tasks (in DL). Healthcare provision and medicine are one of the most significant challenges of AI due to being the pillars for a global society and the necessity of providing higher-quality assistance to the healthcare workforce [2]. An emerging and expanding domain for for application of AI is mental health. Readily available and ubiquitous devices and applications enable the provision of flexible mental care - on-demand, at any time, both at healthcare facilities and at home.