Analysis of survival-related factors in patients with endometrial cancer using a Bayesian network model

The findings indicate that the Bayesian network model is preferable to the Cox proportional hazards model for predicting survival in patients with endometrial cancer.

Authors

Huan Zhang
Shan Zhao (ORCID: https://orcid.org/0000-0001-8285-2730)
Pengzhong Lv

Institutions

Shandong Provincial QianFoShan Hospital (CN)
Shandong First Medical University (CN)

Publication Details

Journal: PLoS ONE
Published: 2024-11-21
DOI: https://doi.org/10.1371/journal.pone.0314018
Citations: 2
Primary Topic: Bayesian Modeling and Causal Inference
Type: article
Field-Weighted Citation Impact: 0.69

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article

Analysis of survival-related factors in patients with endometrial cancer using a Bayesian network model

Huan Zhang, Shan Zhao, Pengzhong Lv

Nov 21, 2024

2 citations

PLoS ONE

Bayesian Modeling and Causal Inference

0.69

article

Analysis of survival-related factors in patients with endometrial cancer using a Bayesian network model

Huan Zhang, Shan Zhao, Pengzhong Lv

November 21, 2024article en

2 citations

Abstract

The findings indicate that the Bayesian network model is preferable to the Cox proportional hazards model for predicting survival in patients with endometrial cancer.

PLoS ONEVol. 19(11)

Shandong Provincial QianFoShan Hospital (CN), Shandong First Medical University (CN)

Good health and well-being

Openalex Percentile: Top 23%

Bayesian Modeling and Causal Inference

0.69

DOI Open Access PDF OpenAlex

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Analysis of survival-related factors in patients with endometrial cancer using a Bayesian network model — Huan Zhang, Shan Zhao, et al. · PLoS ONE (2024) | TGRS Research Map | TGRS