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A semi-supervised learning approach for bladder cancer grading

Recent advances in semi-supervised learning algorithms (SSL) have made great strides in reducing the training dependency on labeled datasets and requiring that only a subset of the data be labeled. The presented work explores a class of semi-supervised learning algorithms that uses consistency regul...

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Autori principali: Kenneth Wenger, Kayvan Tirdad, Alex Dela Cruz, Andrea Mari, Mayada Basheer, Cynthia Kuk, Bas W.G. van Rhijn, Alexandre R. Zlotta, Theodorus H. van der Kwast, Alireza Sadeghian
Natura: Artigo
Lingua:Inglês
Pubblicazione: Elsevier 2022-09-01
Serie:Machine Learning with Applications
Soggetti:
Artificial intelligence
Deep learning
Semi-supervised learning
Pathology
Medical digital imaging
Accesso online:http://www.sciencedirect.com/science/article/pii/S2666827022000512
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