File Download
  Links for fulltext
     (May Require Subscription)

Article: Artificial intelligence in healthcare: Past, present and future

TitleArtificial intelligence in healthcare: Past, present and future
Authors
Issue Date2017
PublisherB M J Group. The Journal's web site is located at http://svn.bmj.com/
Citation
Stroke and Vascular Neurology, 2017, v. 2 n. 4, p. 230-243 How to Cite?
AbstractArtificial 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. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017.
Persistent Identifierhttp://hdl.handle.net/10722/261879
ISSN

 

DC FieldValueLanguage
dc.contributor.authorJiang, F-
dc.contributor.authorJiang, Y-
dc.contributor.authorZhi, H-
dc.contributor.authorDong, Y-
dc.contributor.authorLi, H-
dc.contributor.authorMa, S-
dc.contributor.authorDong, Q-
dc.contributor.authorShen, H-
dc.contributor.authorWang, Y-
dc.contributor.authorWang, Y-
dc.date.accessioned2018-09-28T04:49:41Z-
dc.date.available2018-09-28T04:49:41Z-
dc.date.issued2017-
dc.identifier.citationStroke and Vascular Neurology, 2017, v. 2 n. 4, p. 230-243-
dc.identifier.issn2059-8688-
dc.identifier.urihttp://hdl.handle.net/10722/261879-
dc.description.abstractArtificial 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. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017.-
dc.languageeng-
dc.publisherB M J Group. The Journal's web site is located at http://svn.bmj.com/-
dc.relation.ispartofStroke and Vascular Neurology-
dc.rightsStroke and Vascular Neurology. Copyright © B M J Group.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleArtificial intelligence in healthcare: Past, present and future-
dc.typeArticle-
dc.identifier.emailJiang, F: feijiang@hku.hk-
dc.identifier.emailZhi, H: hzhi@hku.hk-
dc.identifier.emailShen, H: haipeng@hku.hk-
dc.identifier.authorityJiang, F=rp02185-
dc.identifier.authorityShen, H=rp02082-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1136/svn-2017-000101-
dc.identifier.scopuseid_2-s2.0-85050483912-
dc.identifier.hkuros292309-
dc.identifier.hkuros292308-
dc.identifier.volume2-
dc.identifier.issue4-
dc.identifier.spage230-
dc.identifier.epage243-
dc.publisher.placeUnited States-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats