Publication Name	World Journal of Clinical Cases
Manuscript ID	96116
Country	China

Received	2024-04-27 10:32
Peer-Review Started	2024-04-27 10:32
To Make the First Decision
Return for Revision	2024-05-16 01:44
Revised	2024-05-27 04:52
Second Decision	2024-06-17 02:47
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-06-17 09:08
Articles in Press	2024-06-17 09:08
Publication Fee Transferred	2024-06-20 05:20
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-06-28 06:54
Publish the Manuscript Online	2024-07-01 13:38

ISSN	2307-8960 (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/
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Category	Psychology, Clinical
Manuscript Type	Clinical and Translational Research
Article Title	Predicting depression in patients with heart failure based on a stacking model
Manuscript Source	Unsolicited Manuscript
All Author List	Hui Jiang, Rui Hu, Yu-Jie Wang and Xiang Xie
ORCID	Author(s) ORCID Number Hui Jiang http://orcid.org/0009-0002-3164-1559 Xiang Xie http://orcid.org/0000-0001-5514-2362
Funding Agency and Grant Number
Corresponding Author	Xiang Xie, Doctor, Chief Physician, Department of Ultrasound Diagnosis, The second Hospital of Anhui Medical University, NO. 678 Furong Road, Shushan District, Hefei 230601, Anhui Province, China. sonographer@126.com
Key Words	National health and nutrition examination survey; Depression; Heart failure; Stacking ensemble model; Machine learning
Core Tip	In this study, we utilized easily accessible demographic data and laboratory indicators to construct a stacking ensemble model for predicting depression in heart failure patients. We then compared the performance of this stacking model with that of a single machine learning (ML) model and discovered that the stacking model outperformed the single ML model.
Publish Date	2024-07-01 13:38
Citation	<p>Jiang H, Hu R, Wang YJ, Xie X. Predicting depression in patients with heart failure based on a stacking model. <i>World J Clin Cases</i> 2024; 12(21): 4661-4672</p>
URL	https://www.wjgnet.com/2307-8960/full/v12/i21/4661.htm
DOI	https://dx.doi.org/10.12998/wjcc.v12.i21.4661

Full Article (PDF)	WJCC-12-4661-with-cover.pdf
Manuscript File	96116_Auto_Edited-JLW.docx
Answering Reviewers	96116-answering-reviewers.pdf
Audio Core Tip	96116-audio.wav
Biostatistics Review Certificate	96116-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	96116-conflict-of-interest-statement.pdf
Copyright License Agreement	96116-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate	96116-non-native-speakers.pdf
Peer-review Report	96116-peer-reviews.pdf
Scientific Misconduct Check	96116-scientific-misconduct-check.png
Scientific Editor Work List	96116-scientific-editor-work-list.pdf
CrossCheck Report	96116-crosscheck-report.pdf