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Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement
Prediction in health care is closely related with the decision-making process. On the one hand, accurate survivability prediction can help physicians decide between palliative care or other practice for a patient. On the other hand, the notion of remaining lifetime can be an incentive for patients t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163414/ https://www.ncbi.nlm.nih.gov/pubmed/30200676 http://dx.doi.org/10.3390/s18092983 |
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author | Oliveira, Tiago Silva, Ana Satoh, Ken Julian, Vicente Leão, Pedro Novais, Paulo |
author_facet | Oliveira, Tiago Silva, Ana Satoh, Ken Julian, Vicente Leão, Pedro Novais, Paulo |
author_sort | Oliveira, Tiago |
collection | PubMed |
description | Prediction in health care is closely related with the decision-making process. On the one hand, accurate survivability prediction can help physicians decide between palliative care or other practice for a patient. On the other hand, the notion of remaining lifetime can be an incentive for patients to live a fuller and more fulfilling life. This work presents a pipeline for the development of survivability prediction models and a system that provides survivability predictions for years one to five after the treatment of patients with colon or rectal cancer. The functionalities of the system are made available through a tool that balances the number of necessary inputs and prediction performance. It is mobile-friendly and facilitates the access of health care professionals to an instrument capable of enriching their practice and improving outcomes. The performance of survivability models was compared with other existing works in the literature and found to be an improvement over the current state of the art. The underlying system is capable of recalculating its prediction models upon the addition of new data, continuously evolving as time passes. |
format | Online Article Text |
id | pubmed-6163414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61634142018-10-10 Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement Oliveira, Tiago Silva, Ana Satoh, Ken Julian, Vicente Leão, Pedro Novais, Paulo Sensors (Basel) Article Prediction in health care is closely related with the decision-making process. On the one hand, accurate survivability prediction can help physicians decide between palliative care or other practice for a patient. On the other hand, the notion of remaining lifetime can be an incentive for patients to live a fuller and more fulfilling life. This work presents a pipeline for the development of survivability prediction models and a system that provides survivability predictions for years one to five after the treatment of patients with colon or rectal cancer. The functionalities of the system are made available through a tool that balances the number of necessary inputs and prediction performance. It is mobile-friendly and facilitates the access of health care professionals to an instrument capable of enriching their practice and improving outcomes. The performance of survivability models was compared with other existing works in the literature and found to be an improvement over the current state of the art. The underlying system is capable of recalculating its prediction models upon the addition of new data, continuously evolving as time passes. MDPI 2018-09-06 /pmc/articles/PMC6163414/ /pubmed/30200676 http://dx.doi.org/10.3390/s18092983 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Oliveira, Tiago Silva, Ana Satoh, Ken Julian, Vicente Leão, Pedro Novais, Paulo Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement |
title | Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement |
title_full | Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement |
title_fullStr | Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement |
title_full_unstemmed | Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement |
title_short | Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement |
title_sort | survivability prediction of colorectal cancer patients: a system with evolving features for continuous improvement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163414/ https://www.ncbi.nlm.nih.gov/pubmed/30200676 http://dx.doi.org/10.3390/s18092983 |
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