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Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Master Publishing Group
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614841/ https://www.ncbi.nlm.nih.gov/pubmed/23675244 |
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author | Takehira, Rieko Murakami, Keiko Katayama, Sirou Nishizawa, Kenji Yamamura, Shigeo |
author_facet | Takehira, Rieko Murakami, Keiko Katayama, Sirou Nishizawa, Kenji Yamamura, Shigeo |
author_sort | Takehira, Rieko |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3614841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Master Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-36148412013-05-01 Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses Takehira, Rieko Murakami, Keiko Katayama, Sirou Nishizawa, Kenji Yamamura, Shigeo Int J Biomed Sci Article 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. Master Publishing Group 2011-12 /pmc/articles/PMC3614841/ /pubmed/23675244 Text en © Rieko Takehira et al. Licensee Master Publishing Group http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Article Takehira, Rieko Murakami, Keiko Katayama, Sirou Nishizawa, Kenji Yamamura, Shigeo Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses |
title | Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses |
title_full | Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses |
title_fullStr | Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses |
title_full_unstemmed | Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses |
title_short | Artificial Neural Network Modeling of Quality of Life of Cancer Patients: Relationships between Quality of Life Assessments, as Evaluated by Patients, Pharmacists, and Nurses |
title_sort | artificial neural network modeling of quality of life of cancer patients: relationships between quality of life assessments, as evaluated by patients, pharmacists, and nurses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614841/ https://www.ncbi.nlm.nih.gov/pubmed/23675244 |
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