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Artificial intelligence in healthcare: past, present and future

by Jiang, Yong , Dong, Yi , Wang, Yilong , Jiang, Fei , Ma, Sufeng , Dong, Qiang , Shen, Haipeng , Zhi, Hui , Li, Hao , Wang, Yongjun

in Algorithms / Artificial intelligence / Artificial Intelligence - history / Artificial Intelligence - trends / Cancer / Clinical decision making / Clinical medicine / Clustering / Congenital diseases / Data analysis / Data Mining - history / Data Mining - trends / Deep learning / Delivery of Health Care - history / Delivery of Health Care - trends / Diabetic retinopathy / Diagnosis, Computer-Assisted - history / Diagnosis, Computer-Assisted - trends / Diffusion of Innovation / Disease / Early Diagnosis / Electronic health records / Forecasting / History, 20th Century / History, 21st Century / Humans / Machine learning / Medical equipment / Medical laboratories / Medical prognosis / Medical records / Natural language processing / Patients / Physicians / Predictive Value of Tests / Principal components analysis / Prognosis / Review / Stroke - diagnosis / Stroke - history / Stroke - physiopathology / Stroke - therapy / Therapy, Computer-Assisted - history / Therapy, Computer-Assisted - trends

2017

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Artificial intelligence in healthcare: past, present and future

by Jiang, Yong , Dong, Yi , Wang, Yilong , Jiang, Fei , Ma, Sufeng , Dong, Qiang , Shen, Haipeng , Zhi, Hui , Li, Hao , Wang, Yongjun

2017

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Artificial intelligence in healthcare: past, present and future

by Jiang, Yong , Dong, Yi , Wang, Yilong , Jiang, Fei , Ma, Sufeng , Dong, Qiang , Shen, Haipeng , Zhi, Hui , Li, Hao , Wang, Yongjun

2017

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Journal Article

Artificial intelligence in healthcare: past, present and future

Jiang, Yong,

Dong, Yi,

Wang, Yilong,

Jiang, Fei,

Ma, Sufeng,

Dong, Qiang,

Shen, Haipeng,

Zhi, Hui,

Li, Hao,

Wang, Yongjun

2017

Overview

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.

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Publisher

BMJ Publishing Group LTD,BMJ Publishing Group

Subject

Algorithms

/ Artificial intelligence

/ Artificial Intelligence - history

/ Artificial Intelligence - trends

/ Cancer

/ Clinical decision making

/ Clinical medicine