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Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement

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Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement

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Oliveira, T.; Silva, A.; Satoh, K.; Julian Inglada, VJ.; Leao, P.; Novais, P. (2018). Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement. Sensors. 18(9). https://doi.org/10.3390/s18092983

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Título: Survivability Prediction of Colorectal Cancer Patients: A System with Evolving Features for Continuous Improvement
Autor: Oliveira, Tiago Silva, Ana Satoh, Ken Julian Inglada, Vicente Javier Leao, Pedro Novais, Paulo
Entidad UPV: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Fecha difusión:
Resumen:
[EN] 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 ...[+]
Palabras clave: Survivability prediction , Clinical decision support , Machine learning
Derechos de uso: Reconocimiento (by)
Fuente:
Sensors. (eissn: 1424-8220 )
DOI: 10.3390/s18092983
Editorial:
MDPI AG
Versión del editor: https://doi.org/10.3390/s18092983
Código del Proyecto:
info:eu-repo/grantAgreement/JSPS//JP18K18115/
Agradecimientos:
The work of Tiago Oliveira was supported by JSPS KAKENHI Grant Number JP18K18115.
Tipo: Artículo

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