Cross-hospital portability of information extraction of cancer staging information
We evaluate the portability across hospitals of machine learning-based text mining systems for colorectal cancer staging (TNM and ACPS). We present an architecture based on feature selection that allows to build a portable classifier with minimum cost, and we reach state-of-the-art performance. The results show that it is feasible to apply an existing TNM classifier to a new hospital without extra training, given that there is a feature normalisation step.
information extraction text mining colorectal cancer machine learning cancer staging detection