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Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method
Prostate cancer (PCa) is one of the main diseases that endanger men's health worldwide. In developing countries, due to the large number of patients and the lack of medical resources, there is a big conflict between doctors and patients. To solve this problem, an auxiliary medical decision syst...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251439/ https://www.ncbi.nlm.nih.gov/pubmed/32508976 http://dx.doi.org/10.1155/2020/6509596 |
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author | Wu, Jia Zhuang, Qinghe Tan, Yanlin |
author_facet | Wu, Jia Zhuang, Qinghe Tan, Yanlin |
author_sort | Wu, Jia |
collection | PubMed |
description | Prostate cancer (PCa) is one of the main diseases that endanger men's health worldwide. In developing countries, due to the large number of patients and the lack of medical resources, there is a big conflict between doctors and patients. To solve this problem, an auxiliary medical decision system for prostate cancer was constructed. The system used six relevant tumor markers as the input features and employed classical machine learning models (support vector machine and artificial neural network). Stacking method aimed at different ensemble models together was used for the reduction of overfitting. 1,933,535 patient information items had been collected from three first-class hospitals in the past five years to train the model. The result showed that the auxiliary medical system could make use of massive data. Its performance is continuously improved as the amount of data increases. Based on the system and collected data, statistics on the incidence of prostate cancer in the past five years were carried out. In the end, influence of diet habit and genetic inheritance for prostate cancer was analyzed. Results revealed the increasing prevalence of PCa and great negative impact caused by high-fat diet and genetic inheritance. |
format | Online Article Text |
id | pubmed-7251439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-72514392020-06-06 Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method Wu, Jia Zhuang, Qinghe Tan, Yanlin Comput Math Methods Med Research Article Prostate cancer (PCa) is one of the main diseases that endanger men's health worldwide. In developing countries, due to the large number of patients and the lack of medical resources, there is a big conflict between doctors and patients. To solve this problem, an auxiliary medical decision system for prostate cancer was constructed. The system used six relevant tumor markers as the input features and employed classical machine learning models (support vector machine and artificial neural network). Stacking method aimed at different ensemble models together was used for the reduction of overfitting. 1,933,535 patient information items had been collected from three first-class hospitals in the past five years to train the model. The result showed that the auxiliary medical system could make use of massive data. Its performance is continuously improved as the amount of data increases. Based on the system and collected data, statistics on the incidence of prostate cancer in the past five years were carried out. In the end, influence of diet habit and genetic inheritance for prostate cancer was analyzed. Results revealed the increasing prevalence of PCa and great negative impact caused by high-fat diet and genetic inheritance. Hindawi 2020-05-18 /pmc/articles/PMC7251439/ /pubmed/32508976 http://dx.doi.org/10.1155/2020/6509596 Text en Copyright © 2020 Jia Wu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wu, Jia Zhuang, Qinghe Tan, Yanlin Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method |
title | Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method |
title_full | Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method |
title_fullStr | Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method |
title_full_unstemmed | Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method |
title_short | Auxiliary Medical Decision System for Prostate Cancer Based on Ensemble Method |
title_sort | auxiliary medical decision system for prostate cancer based on ensemble method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251439/ https://www.ncbi.nlm.nih.gov/pubmed/32508976 http://dx.doi.org/10.1155/2020/6509596 |
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