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. 2011 Dec;7(4):255-62.

Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses

Rieko Takehira  1 , Keiko Murakami, Sirou Katayama, Kenji Nishizawa, Shigeo Yamamura
Affiliations

Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses

Rieko Takehira et al. Int J Biomed Sci. 2011 Dec.

Abstract

Aim: The purpose of this study was to investigate the difference between the professional perspectives of pharmacists and nurses in Japan with regard to evaluation of the quality of life (QOL) of cancer patients.

Methods: A group of cancer hospital inpatients (n=15) were asked to rate the condition of their health and their QOL by filling in a questionnaire. On the same day, a group of pharmacists (n=8) and nurses (n=18) also evaluated patient QOL. Three-layered artificial neural network (ANN) architecture was used to model the relationship between the different QOL evaluations made by patients, pharmacists, and nurses.

Results: Although there was no statistical difference between the QOL scores obtained from pharmacists and nurses, the correlation between these scores was weak (0.1188). These results suggest that pharmacists and nurses evaluate the QOL of their patients from different perspectives, based on their respective profession. QOL parameters were modeled with an ANN using the scores, given by patients in answer to questions regarding health-related QOL as input variables. Both the predictive performance of the ANN and the robustness of the optimized model were acceptable. The response surfaces calculated by ANN modeling showed that pharmacists and nurses evaluate patient's QOL using different information and reasoning, which is likely related to the nature of their contact with the patients.

Conclusion: Health professionals evaluate patient QOL from different perspectives, depending on their profession.

Keywords: neural network; nurse; pharmacist; profession; quality of life.

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Figures

Figure 1
Figure 1
ANN diagram to model the QOL of cancer patients.
Figure 2
Figure 2
Change of prediction performance of QOL with number of neurons in hidden layer.
Figure 3
Figure 3
Response surface of input parameters and QOLs obtained from ANN model. Q1 (Did you sleep well?)-Q8 (Were you able to move freely to a rest room without assistance?)-QOL. (A), evaluated by pharmacists; (B), evaluated by nurses.
Figure 4
Figure 4
Response surface of input parameters and QOLs obtained from ANN model. Q2 (Do you worry about your pain and/or nausea?)-Q6 (Rate of your pain)-QOL. (a), evaluated by pharmacists; (b), evaluated by nurses.
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