Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care

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Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care

Background: Quality of cancer care may greatly impact upon patients’ health-related quality of life (HRQoL). Free-text responses to patient-reported outcome measures (PROMs) provide rich data but analysis is time and resource-intensive. This study developed and tested a learning-based text-mining ap...

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Bibliographic Details
Main Authors:	Wagland, Richard, Recio Saucedo, Alejandra, Simon, Michael, Bracher, Michael, Hunt, Katherine, Foster, Claire, Downing, Amy, Glaser, Adam W., Corner, Jessica
Format:	Article
Published:	BMJ Publishing Group 2015
Subjects:	RC 254 Neoplasms. Tumors. Oncology (including Cancer) RT Nursing text-mining PROMs quality of life colorectal cancer machine learning machine learning algorithms thematic analysis thematic content analysis qualitative methods
Online Access:	https://eprints.nottingham.ac.uk/32437/

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