PT - JOURNAL ARTICLE AU - Jiang, Fei AU - Jiang, Yong AU - Zhi, Hui AU - Dong, Yi AU - Li, Hao AU - Ma, Sufeng AU - Wang, Yilong AU - Dong, Qiang AU - Shen, Haipeng AU - Wang, Yongjun TI - Artificial intelligence in healthcare: past, present and future AID - 10.1136/svn-2017-000101 DP - 2017 Dec 01 TA - Stroke and Vascular Neurology PG - 230--243 VI - 2 IP - 4 4099 - http://svn.bmj.com/content/2/4/230.short 4100 - http://svn.bmj.com/content/2/4/230.full AB - Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.