Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data

Patients with hepatocellular carcinoma require regular follow-up. Here, using Cox-based feature selection to identify key prognostic features, the authors convert time-series follow-up data into a cascading survival map, and show that the approach improves dynamic prognosis prediction for patients.

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Autores principales:	Lujun Shen, Qi Zeng, Pi Guo, Jingjun Huang, Chaofeng Li, Tao Pan, Boyang Chang, Nan Wu, Lewei Yang, Qifeng Chen, Tao Huang, Wang Li, Peihong Wu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/da859ea395f4437b8d38707d5828dc84
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spelling	oai:doaj.org-article:da859ea395f4437b8d38707d5828dc842021-12-02T16:49:35ZDynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data10.1038/s41467-018-04633-72041-1723https://doaj.org/article/da859ea395f4437b8d38707d5828dc842018-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-04633-7https://doaj.org/toc/2041-1723Patients with hepatocellular carcinoma require regular follow-up. Here, using Cox-based feature selection to identify key prognostic features, the authors convert time-series follow-up data into a cascading survival map, and show that the approach improves dynamic prognosis prediction for patients.Lujun ShenQi ZengPi GuoJingjun HuangChaofeng LiTao PanBoyang ChangNan WuLewei YangQifeng ChenTao HuangWang LiPeihong WuNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-10 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Lujun Shen Qi Zeng Pi Guo Jingjun Huang Chaofeng Li Tao Pan Boyang Chang Nan Wu Lewei Yang Qifeng Chen Tao Huang Wang Li Peihong Wu Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
description	Patients with hepatocellular carcinoma require regular follow-up. Here, using Cox-based feature selection to identify key prognostic features, the authors convert time-series follow-up data into a cascading survival map, and show that the approach improves dynamic prognosis prediction for patients.
format	article
author	Lujun Shen Qi Zeng Pi Guo Jingjun Huang Chaofeng Li Tao Pan Boyang Chang Nan Wu Lewei Yang Qifeng Chen Tao Huang Wang Li Peihong Wu
author_facet	Lujun Shen Qi Zeng Pi Guo Jingjun Huang Chaofeng Li Tao Pan Boyang Chang Nan Wu Lewei Yang Qifeng Chen Tao Huang Wang Li Peihong Wu
author_sort	Lujun Shen
title	Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
title_short	Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
title_full	Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
title_fullStr	Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
title_full_unstemmed	Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
title_sort	dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/da859ea395f4437b8d38707d5828dc84
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Dynamically prognosticating patients with hepatocellular carcinoma through survival paths mapping based on time-series data

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