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10.1136/svn-2017-000101 http://scihub22266oqcxt.onion/10.1136/svn-2017-000101 C5829945!5829945!29507784     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Stroke+Vasc+Neurol 2017 ; 2 (4): 230-43 Nephropedia Template TP {{tp|p=29507784|t=2017. Artificial intelligence in healthcare: past, present and future |pdf=|usr=}}{{29507784}} gab.com Text Artificial intelligence in healthcare: past, present and future JO: Stroke Vasc Neurol http://www.kidney.de/pget.php?&tw=1&pmid=29507784 #FOAvip 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. Twit Text FOAVip Artificial intelligence in healthcare: past, present and future ????Stroke Vasc Neurol http://www.kidney.de/pget.php?&tw=1&pmid=29507784 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29507784 #FOAvip English Wikipedia <ref>{{Cite pmid|29507784}}</ref> Artificial intelligence in healthcare: past, present and future #MMPMID29507784 Jiang F; Jiang Y; Zhi H; Dong Y; Li H; Ma S; Wang Y; Dong Q; Shen H; Wang Y Stroke Vasc Neurol 2017[Dec]; 2 (4): 230-43 PMID29507784show ga 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. äArtificial intelligence in healthcare: past, present and future (epmc).pdf DeepDyve Pubget Overpricing