Cross-hospital portability of information extraction of cancer staging information

作者：

Highlights：

• 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.

摘要

Highlights•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.

论文关键词：Machine learning,Text mining,Information extraction,Cancer staging detection,Colorectal cancer

论文评审过程：Received 18 November 2013, Revised 14 June 2014, Accepted 16 June 2014, Available online 21 June 2014.

论文官网地址：https://doi.org/10.1016/j.artmed.2014.06.002