McIntosh Andrew M, Stewart Robert, John Ann, Smith Daniel J, Davis Katrina, Sudlow Cathie, Corvin Aiden, Nicodemus Kristin K, Kingdon David, Hassan Lamiece, Hotopf Matthew, Lawrie Stephen M, Russ Tom C, Geddes John R, Wolpert Miranda, Wölbert Eva, Porteous David J
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Lancet Psychiatry. 2016 Oct;3(10):993-998. doi: 10.1016/S2215-0366(16)30089-X.
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.
数据科学利用计算机科学和统计学从高维数据集中提取新知识(即具有许多不同变量和数据类型的数据集)。心理健康研究、诊断和治疗可以从使用队列研究、基因组学以及常规医疗保健和管理数据的数据科学中受益。英国有很好的条件通过强大的与国民保健服务体系(NHS)相关的数据科学项目来试验这些方法,如英国生物银行、苏格兰世代研究以及临床记录交互式搜索(CRIS)项目。数据科学作为一种低成本、高回报的催化剂,在改善心理健康识别、理解、支持和成果方面具有巨大潜力。从此类研究中吸取的经验教训可能具有全球影响。