Multiobjective semisupervised learning with a right‐censored endpoint adapted to the multiple imputation framework-Reference-Cited by-同舟云学术

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Multiobjective semisupervised learning with a right‐censored endpoint adapted to the multiple imputation framework

Published:2021-06-27 Issue: Volume: Page:
ISSN:0323-3847
Container-title:Biometrical Journal
language:en
Short-container-title:Biometrical Journal

Author:

Faucheux Lilith¹²^ORCID,Soumelis Vassili²³^ORCID,Chevret Sylvie¹⁴^ORCID

Affiliation:

1. Université de Paris Statistic and epidemiologic research center INSERM UMR‐1153, ECSTRRA Team Paris France

2. Université de Paris INSERM U976 Paris France

3. Laboratoire d'immunologie, biologie et histocompatibilité AP‐HP, Hôpital Saint‐Louis Paris France

4. Service de Biostatistique et Information Médicale AP‐HP, Hôpital Saint‐Louis Paris France

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bimj.202000365

Reference52 articles.

1. Towards clinically more relevant dissection of patient heterogeneity via survival-based Bayesian clustering

2. Al‐Najdi A. Pasquier N. &Precioso F.(2016).Frequent closed patterns based multiple consensus clustering. InL.Rutkowski M.Korytkowski R.Scherer R.Tadeusiewicz L. A.Zadeh &J. M.Zurada(Eds.) International Conference on Artificial Intelligence and Soft Computing Springer International Publishing pp.14–26.

3. Data Classification

4. Semi-supervised clustering methods

5. Semi-Supervised Methods to Predict Patient Survival from Gene Expression Data

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparison of characteristics and laboratory tests of COVID-19 hematological patients from France and Brazil during the pre-vaccination period: identification of prognostic profiles for survival;Hematology, Transfusion and Cell Therapy;2022-06

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