Self-supervised learning for medical image classification: a systematic review and implementation gu...
Self-supervised learning for medical image classification: a systematic review and implementation guidelines
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London: Nature Publishing Group UK
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Language
English
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London: Nature Publishing Group UK
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Advancements in deep learning and computer vision provide promising solutions for medical image analysis, potentially improving healthcare and patient outcomes. However, the prevailing paradigm of training deep learning models requires large quantities of labeled training data, which is both time-consuming and cost-prohibitive to curate for medical...
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Self-supervised learning for medical image classification: a systematic review and implementation guidelines
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TN_cdi_doaj_primary_oai_doaj_org_article_9b6f3e412f324b4cbab8e2c3411223a5
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_9b6f3e412f324b4cbab8e2c3411223a5
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ISSN
2398-6352
E-ISSN
2398-6352
DOI
10.1038/s41746-023-00811-0
