Year: 2025
Type: editorial
Abstract: Mental health is essential for overall wellbeing, enabling individuals to cope with daily challenges and participate fully in society. Globally, nearly one billion people are affected by mental health conditions, including rising rates of depression, anxiety, autism, and dementia. In countries like Aotearoa New Zealand, approximately 26% of the population experiences poor mental wellbeing. However, traditional approaches to diagnosis and treatment often fall short due to limited resources and access to care, prompting a shift toward digital health solutions. This editorial explores how big data and artificial intelligence (AI) are transforming mental health research and care. These technologies offer new possibilities for early detection, scalable interventions, and personalised support addressing gaps in existing systems. We highlight key use cases across depression, autism, and dementia, where AI-driven tools are already showing promise in screening and supporting decision-making. We also examine AI applications in detecting depression, autism, and dementia, and the role of chatbot-based tools. The editorial also explores key challenges such as ethical concerns, data bias, and integration into healthcare systems, highlighting the need for responsible and inclusive AI development.
DOI: 10.57129/001c.144915
Authors: Dushanthi M Manamalage, Rabia N Rao, Muhammad Bilal, Gary Cheung, Hiran Thabrew, Partha S Roop, Seyed R Shahamiri, Frederick Sundram
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414582126