Chapter 14: Interpretable semisupervised classifier for predicting cancer stages
Isel Graua; Dipankar Senguptaa,b; Ann Nowea a Artificial Intelligence Lab, Free University of Brussels (VUB), Brussels, Belgiumb PGJCCR, Queens University Belfast, Belfast, United Kingdom
Abstract
Machine learning techniques in medicine have been at the forefront addressing challenges such as diagnosis, prognosis prediction, or precision medicine. In this field, the data are sometimes abundant but comes from different data sources or lack assigned labels. The process of manually labeling these data when conforming to a curated dataset for supervised classification can be costly. Semisupervised classification offers a wide range of methods for leveraging ...
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