Publication Name	World Journal of Methodology
Manuscript ID	91058
Country	India

Received	2023-12-21 00:28
Peer-Review Started	2023-12-21 00:28
To Make the First Decision
Return for Revision	2024-01-14 09:37
Revised	2024-01-28 23:51
Second Decision	2024-03-21 02:48
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-03-21 11:20
Articles in Press	2024-03-21 11:20
Publication Fee Transferred
Edit the Manuscript by Language Editor	2024-03-26 22:43
Typeset the Manuscript	2024-06-11 02:19
Publish the Manuscript Online	2024-06-25 09:25

ISSN	2222-0682 (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: http://creativecommons.org/licenses/by-nc/4.0/
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Category	Infectious Diseases
Manuscript Type	Observational Study
Article Title	Ensemble for evaluating diagnostic efficacy of non-invasive indices in predicting liver fibrosis in untreated hepatitis C virus population
Manuscript Source	Invited Manuscript
All Author List	Navneet Kaur, Gitanjali Goyal, Ravinder Garg, Chaitanya Tapasvi and Umit Demirbaga
ORCID	Author(s) ORCID Number Navneet Kaur http://orcid.org/0000-0002-1766-1636 Gitanjali Goyal http://orcid.org/0000-0002-2105-1312 Ravinder Garg http://orcid.org/0000-0003-0916-2412 Chaitanya Tapasvi http://orcid.org/0000-0002-0244-1200 Umit Demirbaga http://orcid.org/0000-0001-5159-0723
Funding Agency and Grant Number
Corresponding Author	Navneet Kaur, MSc, Research Fellow, Biochemistry, Guru Gobind Singh Medical College and Hospital, Sadiq Road, Faridkot- 151203, Faridkot 151203, Punjab, India. navmann23@yahoo.com
Key Words	Hepatitis C virus; Non-invasive biomarkers; Shear wave elastography; Fibronectin; Bayesian network; Machine learning; Liver fibrosis
Core Tip	The role of non-invasive indices (including serum fibronectin) was investigated to assess and differentiate liver fibrosis in untreated hepatitis C virus (HCV)-infected patients. The overall assessment and prediction process involved the correlation of fibronectin, alanine aminotransferase ratio, aspartate aminotransferase to platelet ratio index, and fibrosis-4 with severity staging performed through shear wave elastography. The role of non-invasive indices to assess and differentiate liver fibrosis is further validated through the calculation of diagnostic accuracy measured using various standard methods such as, sensitivity and specificity, Youden's index, area under receiver operating characteristic curve, and likelihood test. We have explored machine learning-based analysis using a Bayesian Network to predict and validate the diagnostic ability of non-invasive indices for predicting liver fibrosis in HCV patients.
Publish Date	2024-06-25 09:25
Citation	<p>Kaur N, Goyal G, Garg R, Tapasvi C, Demirbaga U. Ensemble for evaluating diagnostic efficacy of non-invasive indices in predicting liver fibrosis in untreated hepatitis C virus population. <i>World J Methodol</i> 2024; 14(3): 91058</p>
URL	https://www.wjgnet.com/2222-0682/full/v14/i3/91058.htm
DOI	https://dx.doi.org/10.5662/wjm.v14.i3.91058

Full Article (PDF)	WJM-14-91058-with-cover.pdf
STROBE Statement	91058-STROBE-statement.pdf
Manuscript File	91058-Review-FilipodiaCL.docx
Answering Reviewers	91058-answering-reviewers.pdf
Audio Core Tip	91058-audio.m4a
Biostatistics Review Certificate	91058-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	91058-conflict-of-interest-statement.pdf
Copyright License Agreement	91058-copyright-assignment.pdf
Signed Informed Consent Form(s) or Document(s)	91058-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document	91058-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate	91058-non-native-speakers.pdf
Peer-review Report	91058-peer-reviews.pdf
Scientific Misconduct Check	91058-scientific-misconduct-check.png
Scientific Misconduct Check	91058-scientific-misconduct-check.png
Scientific Editor Work List	91058-scientific-editor-work-list.pdf
CrossCheck Report	91058-crosscheck-report.pdf