Background Anxiety and depression are the most common mental disorders worldwide.
Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence …

The use of digital tools to measure physiological and behavioural variables of potential
relevance to mental health is a growing field sitting at the intersection between computer …

Advances in large language models (LLMs) have empowered a variety of applications.
However, there is still a significant gap in research when it comes to understanding and …

Despite the plethora of telehealth applications to assist home-based older adults and
healthcare providers, basic messaging and phone calls are still the most common …

Given the limitations of traditional approaches, wearable artificial intelligence (AI) is one of
the technologies that have been exploited to detect or predict depression. The current …

As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

Explainable AI (XAI) has established itself as an important component of AI-driven
interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives …

Despite a rich history of investigating smartphone overuse intervention techniques, AI-based
just-in-time adaptive intervention (JITAI) methods for overuse reduction are lacking. We …

Recent research has demonstrated the capability of behavior signals captured by
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …

MoodCapture presents a novel approach that assesses depression based on images
automatically captured from the front-facing camera of smartphones as people go about their …