Background: Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and ...
Background: Mindfulness-based interventions (MBIs) are becoming increasingly popular for helping people with physical health conditions. Expanding from traditional face-to-face program delivery, there ...
Background: Patient education is a crucial element within health care. It is a known predictor for increased engagement in shared decision making, improved medication and treatment adherence, higher ...
Background: Digital twins (DTs) are digital representations of real-world systems, enabling advanced simulations, predictive modeling, and real-time optimization in various fields, including health ...
Background: Children and adolescents extensively use the internet in their daily lives, often seeking information related to health and well-being. In modern society, the volume of health information ...
Background: Social determinants of health (SDoH) such as housing insecurity are known to be intricately linked to patients’ health status. More efficient methods for abstracting structured data on ...
Background: Major depression accounts for the greatest burden of all diseases globally. The peak onset of depression occurs between adolescence and young adulthood, and for many individuals, ...
Background: Numerous digital health interventions have been developed for mental health promotion and intervention, including eating disorders. Efficacy of many interventions has been evaluated, yet ...