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https://hdl.handle.net/20.500.14365/859
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Aktolun, Cumali | - |
dc.date.accessioned | 2023-06-16T12:47:45Z | - |
dc.date.available | 2023-06-16T12:47:45Z | - |
dc.date.issued | 2019 | - |
dc.identifier.issn | 1619-7070 | - |
dc.identifier.issn | 1619-7089 | - |
dc.identifier.uri | https://doi.org/10.1007/s00259-019-04593-0 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14365/859 | - |
dc.description.abstract | Artificial intelligence involves a wide range of smart techniques that are applicable to medical services including nuclear medicine. Recent advances in computer power, availability of accumulated digital archives containing large amount of patient images, and records bring new opportunities for the implementation of artificial techniques in nuclear medicine. As a subset of artificial intelligence, machine learning is an emerging tool that can possibly perform many clinical tasks. Nuclear medicine community needs to adapt to this fast approaching smart era, to exploit the opportunities and tackle the problems associated with artificial intelligence tools. It is aimed in this editorial to outline the opportunities and challenges of artificial intelligence applications in nuclear medicine. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartof | European Journal of Nuclear Medıcıne And Molecular Imagıng | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject | Radiomics | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Deep learning | en_US |
dc.subject | Artificial neural networks | en_US |
dc.subject | Supervised learning | en_US |
dc.subject | Unsupervised learning | en_US |
dc.subject | Radiology | en_US |
dc.subject | Future | en_US |
dc.title | Artificial Intelligence and Radiomics in Nuclear Medicine: Potentials and Challenges | en_US |
dc.type | Editorial Material | en_US |
dc.identifier.doi | 10.1007/s00259-019-04593-0 | - |
dc.identifier.pmid | 31673788 | - |
dc.identifier.scopus | 2-s2.0-85074721035 | - |
dc.department | İzmir Ekonomi Üniversitesi | en_US |
dc.authorid | Aktolun, Cumali/0000-0002-6245-9349 | - |
dc.authorwosid | Aktolun, Cumali/K-8514-2018 | - |
dc.authorscopusid | 56356834500 | - |
dc.identifier.volume | 46 | en_US |
dc.identifier.issue | 13 | en_US |
dc.identifier.startpage | 2731 | en_US |
dc.identifier.endpage | 2736 | en_US |
dc.identifier.wos | WOS:000493503400002 | - |
dc.relation.publicationcategory | Diğer | en_US |
dc.identifier.scopusquality | Q1 | - |
dc.identifier.wosquality | Q1 | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.openairetype | Editorial Material | - |
crisitem.author.dept | 09.02. Internal Sciences | - |
Appears in Collections: | PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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