A pilot study of breast cancer patients: Can machine learning predict healthcare professionals' responses to patient emotions?

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

An increasing amount of evidence demonstrates the importance of patient oriented interaction in the delivery of health care. The reduction in the incidence of negative emotions both enhances patient satisfaction and improves primary outcomes. The Verona coding definitions of emotional sequences (VR-CoDES) is a reliable system for identifying and coding patient emotions and the corresponding HCP responses. Coded transcripts can be used to instruct and guide healthcare professionals (HCPs) and trainees in an objective and evidence driven fashion. Notwithstanding this powerful potential, the use of VR-CoDES remains limited for practical reasons. Firstly, the coding system itself is complex and training is required to ensure consistent transcript annotation. Moreover the process of annotation is time-consuming and laborious even for a trained expert. Recent advances in machine learning, and its use in text analysis in particular,could be an indispensable benefit. The present paper describes the first work in the literature that explores this possibility. In particular, using 86 consultations between radiotherapists and adult female breast cancer patients we evaluate a range of state of the art classifiers in terms of their ability to predict the responses of HCPs to emotional cues and concerns. We demonstrate highly promising performance, with the best classifiers achieving prediction accuracies of over 82%.
Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on Bioinformatics and Computational Biology, BICOB 2017
Subtitle of host publicationHonolulu; United States; 20 March 2017 through 22 March 2017
EditorsOliver Eulenstein, Qin Ding, Hisham Al-Mubaid
PublisherInternational Society for Computers and Their Applications
Pages101-106
ISBN (Electronic)9781943436057
ISBN (Print)9781943436033
Publication statusPublished - 20 Mar 2017
Event9th International Conference on Bioinformatics and Computational Biology - Waikiki Beach Marriott Resort and Spa, Honolulu, United States
Duration: 20 Mar 201722 Mar 2017
Conference number: 9
http://sce.uhcl.edu/bicob17/

Conference

Conference9th International Conference on Bioinformatics and Computational Biology
Abbreviated titleBICOB
Country/TerritoryUnited States
CityHonolulu
Period20/03/1722/03/17
Internet address

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