Data science for mental health: a UK perspective on a global challenge.
McIntosh AM., Stewart R., John A., Smith DJ., Davis K., Sudlow C., Corvin A., Nicodemus KK., Kingdon D., Hassan L., Hotopf M., Lawrie SM., Russ TC., Geddes JR., Wolpert M., Wölbert E., Porteous DJ., MQ Data Science Group None.
Data science uses computer science and statistics to extract new knowledge from high-dimensional datasets (ie, those with many different variables and data types). Mental health research, diagnosis, and treatment could benefit from data science that uses cohort studies, genomics, and routine health-care and administrative data. The UK is well placed to trial these approaches through robust NHS-linked data science projects, such as the UK Biobank, Generation Scotland, and the Clinical Record Interactive Search (CRIS) programme. Data science has great potential as a low-cost, high-return catalyst for improved mental health recognition, understanding, support, and outcomes. Lessons learnt from such studies could have global implications.