Nowadays, rapid advancements in information technology, automated data collection, digital health technology and big data analytics methods have led to integrated approaches that support more effective and proactive mental health care. The intelligent approaches offer new solutions to identifying the individuals most in need of care, forming more reliable diagnoses of mental diseases, triggering the interventions for a population in mental health risk, providing patients the consistently personalized mental healthcare, etc. This research field is intrinsically interdisciplinary, in the sense that many different scientific domains need to work together and develop novel theories that transcend disciplinary boundaries. Since the outbreak of the COVID-19 pandemic, the roles of intelligent approaches to mental healthcare have become even more critical. However, there are still many knowledge gaps regarding how to implement, integrate and best use intelligent approaches to add value to mental healthcare consumers and providers.
The goal of this Research Topic is to examine the innovative and integrated solutions to improve personal/public mental health monitoring and decision-making in health care services. We seek contributions in the form of original research articles and reviews to bridge the advances in interdisciplinary research and the real-world detection, prediction, diagnosis, and prognosis of various mental health risks and diseases. We hope to understand the most effective pathways from research to practical application to accelerate safe, informed and intelligent healthcare decision-making, from implementation, and validation to promotion.
Topics of interest include, but are not limited to:
- novel integrated intelligent methods for personalized mental healthcare;
- data-driven approaches and digitalized technologies for detection, prediction, diagnosis, and rehabilitation of mental disease and precision medicine;
- evidence-based technologies to support health risk identification;
- interdisciplinary research in developing systems for smart mental health monitoring and management;
- effectiveness of telehealth with regard to conventional care practice;
- challenges in the implementation, validation and promotion of intelligent healthcare;
- AI and big data analytics for mental disease prevention and diagnosis;
- human-computer interaction in digital mental health.
Nowadays, rapid advancements in information technology, automated data collection, digital health technology and big data analytics methods have led to integrated approaches that support more effective and proactive mental health care. The intelligent approaches offer new solutions to identifying the individuals most in need of care, forming more reliable diagnoses of mental diseases, triggering the interventions for a population in mental health risk, providing patients the consistently personalized mental healthcare, etc. This research field is intrinsically interdisciplinary, in the sense that many different scientific domains need to work together and develop novel theories that transcend disciplinary boundaries. Since the outbreak of the COVID-19 pandemic, the roles of intelligent approaches to mental healthcare have become even more critical. However, there are still many knowledge gaps regarding how to implement, integrate and best use intelligent approaches to add value to mental healthcare consumers and providers.
The goal of this Research Topic is to examine the innovative and integrated solutions to improve personal/public mental health monitoring and decision-making in health care services. We seek contributions in the form of original research articles and reviews to bridge the advances in interdisciplinary research and the real-world detection, prediction, diagnosis, and prognosis of various mental health risks and diseases. We hope to understand the most effective pathways from research to practical application to accelerate safe, informed and intelligent healthcare decision-making, from implementation, and validation to promotion.
Topics of interest include, but are not limited to:
- novel integrated intelligent methods for personalized mental healthcare;
- data-driven approaches and digitalized technologies for detection, prediction, diagnosis, and rehabilitation of mental disease and precision medicine;
- evidence-based technologies to support health risk identification;
- interdisciplinary research in developing systems for smart mental health monitoring and management;
- effectiveness of telehealth with regard to conventional care practice;
- challenges in the implementation, validation and promotion of intelligent healthcare;
- AI and big data analytics for mental disease prevention and diagnosis;
- human-computer interaction in digital mental health.