Chen Lu, Xia Chunchao, Sun Huaiqiang
West China Medical Publishers, West China Hospital of Sichuan University, Chengdu 610041, China.
Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China.
Precis Clin Med. 2020 Aug 28;3(3):202-213. doi: 10.1093/pcmedi/pbaa029. eCollection 2020 Sep.
Deep learning (DL) is a recently proposed subset of machine learning methods that has gained extensive attention in the academic world, breaking benchmark records in areas such as visual recognition and natural language processing. Different from conventional machine learning algorithm, DL is able to learn useful representations and features directly from raw data through hierarchical nonlinear transformations. Because of its ability to detect abstract and complex patterns, DL has been used in neuroimaging studies of psychiatric disorders, which are characterized by subtle and diffuse alterations. Here, we provide a brief review of recent advances and associated challenges in neuroimaging studies of DL applied to psychiatric disorders. The results of these studies indicate that DL could be a powerful tool in assisting the diagnosis of psychiatric diseases. We conclude our review by clarifying the main promises and challenges of DL application in psychiatric disorders, and possible directions for future research.
深度学习（DL）是机器学习方法中最近提出的一个子集，在学术界引起了广泛关注，在视觉识别和自然语言处理等领域打破了基准记录。与传统机器学习算法不同，深度学习能够通过分层非线性变换直接从原始数据中学习有用的表示和特征。由于其能够检测抽象和复杂的模式，深度学习已被用于精神疾病的神经影像学研究，这些疾病的特点是细微和弥漫性改变。在这里，我们简要回顾了深度学习应用于精神疾病的神经影像学研究的最新进展和相关挑战。这些研究结果表明，深度学习可能是辅助精神疾病诊断的有力工具。我们通过阐明深度学习在精神疾病应用中的主要前景和挑战以及未来研究的可能方向来结束我们的综述。
