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Applying Self-Supervised Learning to Medicine: Review of the State of the Art and Medical Implementations
2021
Informatics
Machine learning has become an increasingly ubiquitous technology, as big data continues to inform and influence everyday life and decision-making. Currently, in medicine and healthcare, as well as in most other industries, the two most prevalent machine learning paradigms are supervised learning and transfer learning. Both practices rely on large-scale, manually annotated datasets to train increasingly complex models. However, the requirement of data to be manually labeled leaves an excess of
doi:10.3390/informatics8030059
fatcat:6osdf2ybknf37ojndtpszshxvy