Can Big Data Help Psychiatry Unravel the Complexity of Mental Illness(中英双语).docx

Can Big Data Help Psychiatry Unravel the Complexity of Mental Illness?大数据能帮助精神病学解开心理疾病的复杂性难题？Brain science draws legions of eager students to the field and countless millions in dollars, euros and renminbi to fund research. These endeavors, however, have not yielded major improvements in treating patients who suffer from psychiatric disorders for decades.脑科学领域吸引大量热心学生，并且投入数百万美元、欧元和人民币来资助本领域研究。但是，这些努力并没有使人们在治疗遭受几十年精神疾病患者方面取得重大突破。The languid pace of translating research into therapies stems from the inherent difficulties in understanding mental illness. “Psychiatry deals with brains interacting with the world and with other brains, so were not just considering a brains function but its function in complex situations,” says of the Swiss Federal Institute of Technology (E.T.H. Zurich) and the University of Zurich, lead author of a review of the emerging field of computational psychiatry, published this month in Nature Neuroscience. Computational psychiatry sets forth the ambitious goal of using sophisticated numerical tools to understand and treat mental illness. [Scientific American is part of Springer Nature.]把以上研究应用于治疗的进展缓慢是由于人们还未充分了解心理疾病。“精神病学研究人脑间及与世界的交互过程，因此，除了考虑人脑功能外，我们还应考虑其在复杂情景下作用”苏黎世联邦理工学院苏及黎世大学Quentin Huys表示，其作为第一作者，在本月《自然》杂志神经科学板块发表了新兴计算精神病学领域评论文章的。计算精神病学提出使用复杂数字工具理解及治疗心理疾病这一宏伟目标：。Psychiatry currently defines disorders using lists of symptoms. Researchers have been devoting enormous energies to find biological markers that make diagnosis more objective with only halting success. Part of the problem is there is usually no one-to-one correspondence between biological causes and disorders defined by their symptoms, such as those in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). A specific disorder, like depression or schizophrenia, may result from a range of different underlying causes (biological or otherwise). On the other hand, the same cause might ultimately lead to different disorders in different people, depending on an