| Literature DB >> 27692269 |
Andrew M McIntosh1, Robert Stewart2, Ann John3, Daniel J Smith4, Katrina Davis2, Cathie Sudlow5, Aiden Corvin6, Kristin K Nicodemus7, David Kingdon8, Lamiece Hassan9, Matthew Hotopf2, Stephen M Lawrie5, Tom C Russ5, John R Geddes10, Miranda Wolpert11, Eva Wölbert12, David J Porteous7.
Abstract
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.Mesh:
Year: 2016 PMID: 27692269 DOI: 10.1016/S2215-0366(16)30089-X
Source DB: PubMed Journal: Lancet Psychiatry ISSN: 2215-0366 Impact factor: 27.083