Publication Name	World Journal of Gastroenterology
Manuscript ID	91903
Country	China

Received	2024-01-09 03:29
Peer-Review Started	2024-01-09 03:29
To Make the First Decision
Return for Revision	2024-05-08 03:04
Revised	2024-05-20 13:47
Second Decision	2024-06-07 02:45
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-06-07 06:28
Articles in Press	2024-06-07 06:28
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-06-18 07:15
Publish the Manuscript Online	2024-07-01 07:39

ISSN	1007-9327 (print) and 2219-2840 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright	© The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher	Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website	http://www.wjgnet.com

Category	Radiology, Nuclear Medicine & Medical Imaging
Manuscript Type	Retrospective Study
Article Title	Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease
Manuscript Source	Unsolicited Manuscript
All Author List	Meng-Jun Xiao, Yu-Teng Pan, Jia-He Tan, Hai-Ou Li and Hai-Yan Wang
ORCID	Author(s) ORCID Number Hai-Yan Wang http://orcid.org/0000-0002-8506-7604
Funding Agency and Grant Number	Funding Agency Grant Number Key Technology Research and Development Program of Shandong Province, China No. 2021SFGC0104
Corresponding Author	Hai-Yan Wang, MD, PhD, Professor, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 324 Jingwu Road, Jinan 250021, Shandong Province, China. whyott@163.com
Key Words	Primary intestinal lymphoma; Crohn's disease; Radiomics; Machine learning; Diagnosis
Core Tip	In the present study employed radiomics to extract features from computed tomography images of primary intestinal lymphoma and Crohn's disease, followed by the construction of machine learning models for improved differentiation between these two conditions. The least absolute shrinkage and selection operator regression model with 5-fold cross validation was utilized for feature selection, resulting in the identification of 13 optimal predictive radiomics features along with 4 clinical features. Ultimately, all phase models incorporating radiomics features and a combined model integrating both radiomics and clinical features were developed.
Publish Date	2024-07-01 07:39
Citation	<p>Xiao MJ, Pan YT, Tan JH, Li HO, Wang HY. Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease. <i>World J Gastroenterol</i> 2024; 30(25): 3155-3165</p>
URL	https://www.wjgnet.com/1007-9327/full/v30/i25/3155.htm
DOI	https://dx.doi.org/10.3748/wjg.v30.i25.3155

Full Article (PDF)	WJG-30-3155-with-cover.pdf
Manuscript File	91903_Auto_Edited-YJP.docx
Answering Reviewers	91903-answering-reviewers.pdf
Audio Core Tip	91903-audio.wav
Biostatistics Review Certificate	91903-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	91903-conflict-of-interest-statement.pdf
Copyright License Agreement	91903-copyright-assignment.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	91903-foundation-statement.pdf
Signed Informed Consent Form(s) or Document(s)	91903-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document	91903-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate	91903-non-native-speakers.pdf
Supplementary Material	91903-supplementary-material.pdf
Peer-review Report	91903-peer-reviews.pdf
Scientific Misconduct Check	91903-scientific-misconduct-check.png
Scientific Editor Work List	91903-scientific-editor-work-list.pdf
CrossCheck Report	91903-crosscheck-report.png
CrossCheck Report	91903-crosscheck-report.pdf