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88

Deep learning algorithms can be applied to unsupervised learning tasks. This is an important benefit because unlabeled data can be more abundant than labeled data. For example, in a clinical environment, a deep learning system with a multi-layered ANN can initially be trained using a classification of outcomes in a supervised fashion. As the data grows, the system can optionally learn in an unsupervised manner, for example by utilizing pattern recognition across large clinical datasets, which can include pre-operative, intra-operative and post-operative data. (See US Patent 11,278,413 Para. 76-79).

Added by DJM Jan 2024