RETRACTION: Brain Tumor Segmentation and Overall Survival Period Prediction in Glioblastoma Multiforme Using Radiomic Features

IF 1.5 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Concurrency and Computation-Practice & Experience Pub Date : 2025-02-18 DOI:10.1002/cpe.70014

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引用次数: 0

Abstract

RETRACTION: S. Das, S. Bose, G. K. Nayak, S. C. Satapathy, and S. Saxena, “ Brain Tumor Segmentation and Overall Survival Period Prediction in Glioblastoma Multiforme Using Radiomic Features,” Concurrency and Computation: Practice and Experience 34, no. 20 (2022): e6501, https://doi.org/10.1002/cpe.6501.

The above article, published online on 21 July 2021 in Wiley Online Library ( wileyonlinelibrary.com), has been retracted by agreement between the journal Editors, David W. Walker, Jinjun Chen, Nitin Auluck, and Martin Berzins; and John Wiley & Sons Ltd. The retraction has been agreed on as the peer review and publishing process was found to be manipulated. Furthermore, the authors included incoherent, meaningless, and irrelevant information in this article. The underlying dataset is not referenced correctly and a detailed description of the applied methods is missing so that the results cannot be considered reproducible. The authors have been informed of the decision to retract.

查看原文本刊更多论文

缩回：利用放射学特征预测多形性胶质母细胞瘤的肿瘤分割和总生存期

引用本文：S. Das， S. Bose， G. K. Nayak， S. C. Satapathy， S. Saxena，“利用放射学特征预测多形性胶质母细胞瘤的肿瘤分割和总生存期”，并行计算与实践，第34期。20 (2022): e6501, https://doi.org/10.1002/cpe.6501.The上述文章于2021年7月21日在线发表在Wiley在线图书馆（wileyonlinelibrary.com）上，经期刊编辑David W. Walker, Jinjun Chen， Nitin Auluck和Martin Berzins同意撤回；约翰·威利&；子有限公司由于发现同行评议和出版过程被操纵，因此已同意撤回。此外，作者在这篇文章中包含了不连贯、无意义和不相关的信息。基础数据集没有被正确引用，并且缺少应用方法的详细描述，因此结果不能被认为是可重复的。作者已被告知撤稿的决定。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Concurrency and Computation-Practice & Experience 工程技术-计算机：理论方法

CiteScore

5.00

自引率

10.00%

发文量

664

审稿时长

9.6 months

期刊介绍： Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.