This article is a correction to:
Neoplastic and Non-neoplastic Acute Intracerebral Hemorrhage in CT Brain Scans: Machine Learning-Based Prediction Using Radiomic Image Features
Jawed Nawabi1*†‡
Helge Kniep1†
Reza Kabiri1
Gabriel Broocks1
Tobias D. Faizy1Christian Thaler1
Gerhard Schön2
Jens Fiehler1
Uta Hanning1- 1Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- 2Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
A Corrigendum on
Neoplastic and Non-neoplastic Acute Intracerebral Hemorrhage in CT Brain Scans: Machine Learning-Based Prediction Using Radiomic Image Features
by Nawabi, J., Kniep, H., Kabiri, R., Broocks, G., Faizy, T. D., Thaler, C., et al. (2020). Front. Neurol. 11:285. doi: 10.3389/fneur.2020.00285
In the original article, there was an error. The article erroneously states that “The data that support the findings of this study are available from the corresponding author upon reasonable request.” Unfortunately, we are unable to provide the full raw data scan set due to the recent implementation of stricter data security regulations by our institution.
A correction has been made to Methods, Paragraph 1. The corrected paragraph is shown below.
This single-center retrospective study was approved by the ethics committee (Ethik-Kommission der Ärztekammer Hamburg, WF-054/19), and written informed consent was waived according to paragraph 9 section 2 of the Hamburg federal state legislation and paragraph 15 section 1 of the medical association's professional code of conduct in Hamburg. All study protocols and procedures were conducted in accordance with the Declaration of Helsinki. The data that support the findings of this study are available, upon reasonable request from the corresponding author, if in accordance with the institution's data security regulations.
The Data Availability Statement has also been updated, as shown below.
Data Availability Statement
The data that support the findings of this study are available, upon reasonable request from the corresponding author, if in accordance with the institution's data security regulations.
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Keywords: intracerebral hemorrhage, neoplastic hemorrhage, radiomics, machine learning, artificial intelligence
Citation: Nawabi J, Kniep H, Kabiri R, Broocks G, Faizy TD, Thaler C, Schön G, Fiehler J and Hanning U (2021) Corrigendum: Neoplastic and Non-neoplastic Acute Intracerebral Hemorrhage in CT Brain Scans: Machine Learning-Based Prediction Using Radiomic Image Features. Front. Neurol. 12:687610. doi: 10.3389/fneur.2021.687610
Received: 29 March 2021; Accepted: 13 April 2021;
Published: 21 May 2021.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2021 Nawabi, Kniep, Kabiri, Broocks, Faizy, Thaler, Schön, Fiehler and Hanning. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jawed Nawabi, jawed.nawabi@charite.de
†These authors have contributed equally to this work
‡ORCID: Jawed Nawabi orcid.org/0000-0002-1137-0643