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https://ahro.austin.org.au/austinjspui/handle/1/25270
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Pedersen, Mangor | - |
dc.contributor.author | Verspoor, Karin | - |
dc.contributor.author | Jenkinson, Mark | - |
dc.contributor.author | Law, Meng | - |
dc.contributor.author | Abbott, David F | - |
dc.contributor.author | Jackson, Graeme D | - |
dc.date | 2020-07-09 | - |
dc.date.accessioned | 2020-11-10T03:07:40Z | - |
dc.date.available | 2020-11-10T03:07:40Z | - |
dc.date.issued | 2020-07-09 | - |
dc.identifier.citation | Brain Communications 2020; 2(2): fcaa096 | en |
dc.identifier.uri | https://ahro.austin.org.au/austinjspui/handle/1/25270 | - |
dc.description.abstract | Artificial intelligence is one of the most exciting methodological shifts in our era. It holds the potential to transform healthcare as we know it, to a system where humans and machines work together to provide better treatment for our patients. It is now clear that cutting edge artificial intelligence models in conjunction with high-quality clinical data will lead to improved prognostic and diagnostic models in neurological disease, facilitating expert-level clinical decision tools across healthcare settings. Despite the clinical promise of artificial intelligence, machine and deep-learning algorithms are not a one-size-fits-all solution for all types of clinical data and questions. In this article, we provide an overview of the core concepts of artificial intelligence, particularly contemporary deep-learning methods, to give clinician and neuroscience researchers an appreciation of how artificial intelligence can be harnessed to support clinical decisions. We clarify and emphasize the data quality and the human expertise needed to build robust clinical artificial intelligence models in neurology. As artificial intelligence is a rapidly evolving field, we take the opportunity to iterate important ethical principles to guide the field of medicine is it moves into an artificial intelligence enhanced future. | en |
dc.language.iso | eng | |
dc.subject | artificial intelligence | en |
dc.subject | augmented intelligence | en |
dc.subject | deep learning | en |
dc.subject | ethics | en |
dc.subject | neurology | en |
dc.title | Artificial intelligence for clinical decision support in neurology. | en |
dc.type | Journal Article | en |
dc.identifier.journaltitle | Brain Communications | en |
dc.identifier.affiliation | Department of Psychology, Auckland University of Technology (AUT), Auckland, 0627, New Zealand | en |
dc.identifier.affiliation | Department of Neuroscience, Monash School of Medicine, Nursing and Health Sciences, Melbourne, VIC 3181, Australia | en |
dc.identifier.affiliation | Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK | en |
dc.identifier.affiliation | South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA 5000, Australia | en |
dc.identifier.affiliation | Australian Institute for Machine Learning (AIML), The University of Adelaide, Adelaide, SA 5000, Australia | en |
dc.identifier.affiliation | Department of Medicine Austin Health, The University of Melbourne, Heidelberg, VIC 3084, Australia | en |
dc.identifier.affiliation | Neurology | en |
dc.identifier.affiliation | Department of Radiology, Alfred Hospital, Melbourne, VIC 3181, Australia | en |
dc.identifier.affiliation | Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3181, Australia | en |
dc.identifier.affiliation | School of Computing and Information Systems, The University of Melbourne, Parkville, VIC 3010, Australia | en |
dc.identifier.affiliation | The Florey Institute of Neuroscience and Mental Health | en |
dc.identifier.doi | 10.1093/braincomms/fcaa096 | en |
dc.type.content | Text | en |
dc.identifier.orcid | 0000-0002-9199-1916 | en |
dc.identifier.orcid | 0000-0002-8661-1544 | en |
dc.identifier.orcid | 0000-0001-6043-0166 | en |
dc.identifier.orcid | 0000-0001-8414-1991 | en |
dc.identifier.orcid | 0000-0002-7259-8238 | en |
dc.identifier.orcid | 0000-0002-7917-5326 | en |
dc.identifier.pubmedid | 33134913 | |
local.name.researcher | Abbott, David F | |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairetype | Journal Article | - |
crisitem.author.dept | The Florey Institute of Neuroscience and Mental Health | - |
crisitem.author.dept | Neurology | - |
crisitem.author.dept | The Florey Institute of Neuroscience and Mental Health | - |
Appears in Collections: | Journal articles |
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