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Machine Learning in the Nuclear Medicine: Part 1-Introduction

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dc.contributor.authorUribe, Carlos F.
dc.contributor.authorMathotaarachchi, Sulantha
dc.contributor.authorGaudet, Vincent C.
dc.contributor.authorSmith, Kenneth C.
dc.contributor.authorRosa-Neto, Pedro
dc.contributor.authorBenard, Francois
dc.contributor.authorBlack, Sandra E.
dc.contributor.authorZukotynski, Katherine
dc.date.accessioned2023-11-03T17:39:00Z
dc.date.available2023-11-03T17:39:00Z
dc.date.issued2019-04
dc.descriptionThis research was originally published in JNM. Uribe, C.F., Mathotaarachchi, S., Gaudet, V., Smith, K.C, Rosa-Neto, P., Benard, F., Black, S.E. & Zukotynski, K. Machine Learning in Nuclear Medicine: Part 1 - Introduction. J Nucl Med. 2019;60:451-458. © SNMMI.en
dc.description.abstractThis article, the first in a 2-part series, provides an introduction to machine learning (ML) in a nuclear medicine context. This part addresses the history of ML and describes common algorithms, with illustrations of when they can be helpful in nuclear medicine. Part 2 focuses on current contributions of ML to our field, addresses future expectations and limitations, and provides a critical appraisal of what ML can and cannot do.en
dc.identifier.urihttps://doi.org/10.2967/jnumed.118.223495
dc.identifier.urihttp://hdl.handle.net/10012/20085
dc.language.isoenen
dc.publisherSociety of Nuclear Medicine and Molecular Imagingen
dc.relation.ispartofseriesJournal of Nuclear Medicine;60(4)
dc.subjectmachine learningen
dc.subjectartificial intelligenceen
dc.subjectnuclear medicineen
dc.subjectalgorithmsen
dc.titleMachine Learning in the Nuclear Medicine: Part 1-Introductionen
dc.typeArticleen
dcterms.bibliographicCitationUribe, C. F., Mathotaarachchi, S., Gaudet, V., Smith, K. C., Rosa-Neto, P., Bénard, F., Black, S. E., & Zukotynski, K. (2019). Machine learning in nuclear medicine: Part 1—introduction. Journal of Nuclear Medicine, 60(4), 451–458. https://doi.org/10.2967/jnumed.118.223495en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Electrical and Computer Engineeringen
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.typeOfResourceTexten

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