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An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network
The incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in recent years, and its mortality rate has become one of the highest among all cancers. CRC also increasingly affects people’s health and quality of life, and the workloads of medical doctors have further increased d...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874645/ https://www.ncbi.nlm.nih.gov/pubmed/31758076 http://dx.doi.org/10.1038/s41598-019-54031-2 |
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author | Wan, Jing-Jing Chen, Bo-Lun Kong, Yi-Xiu Ma, Xing-Gang Yu, Yong-Tao |
author_facet | Wan, Jing-Jing Chen, Bo-Lun Kong, Yi-Xiu Ma, Xing-Gang Yu, Yong-Tao |
author_sort | Wan, Jing-Jing |
collection | PubMed |
description | The incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in recent years, and its mortality rate has become one of the highest among all cancers. CRC also increasingly affects people’s health and quality of life, and the workloads of medical doctors have further increased due to the lack of sufficient medical resources in China. The goal of this study was to construct an automated expert system using a deep learning technique to predict the probability of early stage CRC based on the patient’s case report and the patient’s attributes. Compared with previous prediction methods, which are either based on sophisticated examinations or have high computational complexity, this method is shown to provide valuable information such as suggesting potentially important early signs to assist in early diagnosis, early treatment and prevention of CRC, hence helping medical doctors reduce the workloads of endoscopies and other treatments. |
format | Online Article Text |
id | pubmed-6874645 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68746452019-12-04 An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network Wan, Jing-Jing Chen, Bo-Lun Kong, Yi-Xiu Ma, Xing-Gang Yu, Yong-Tao Sci Rep Article The incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in recent years, and its mortality rate has become one of the highest among all cancers. CRC also increasingly affects people’s health and quality of life, and the workloads of medical doctors have further increased due to the lack of sufficient medical resources in China. The goal of this study was to construct an automated expert system using a deep learning technique to predict the probability of early stage CRC based on the patient’s case report and the patient’s attributes. Compared with previous prediction methods, which are either based on sophisticated examinations or have high computational complexity, this method is shown to provide valuable information such as suggesting potentially important early signs to assist in early diagnosis, early treatment and prevention of CRC, hence helping medical doctors reduce the workloads of endoscopies and other treatments. Nature Publishing Group UK 2019-11-22 /pmc/articles/PMC6874645/ /pubmed/31758076 http://dx.doi.org/10.1038/s41598-019-54031-2 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Wan, Jing-Jing Chen, Bo-Lun Kong, Yi-Xiu Ma, Xing-Gang Yu, Yong-Tao An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network |
title | An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network |
title_full | An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network |
title_fullStr | An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network |
title_full_unstemmed | An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network |
title_short | An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network |
title_sort | early intestinal cancer prediction algorithm based on deep belief network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874645/ https://www.ncbi.nlm.nih.gov/pubmed/31758076 http://dx.doi.org/10.1038/s41598-019-54031-2 |
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