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Articles Published Processes
1/14/2026 8:39:33 AM | Browse: 0 | Download: 0
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Received |
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2025-09-09 02:22 |
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Peer-Review Started |
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2025-09-09 02:22 |
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First Decision by Editorial Office Director |
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2025-09-25 08:17 |
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Return for Revision |
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2025-09-25 08:17 |
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Revised |
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2025-10-08 09:56 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2025-12-23 02:35 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2025-12-23 06:27 |
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Articles in Press |
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2025-12-23 06:27 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-01-07 00:25 |
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Publish the Manuscript Online |
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2026-01-14 08:39 |
| ISSN |
2220-3230 (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) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Transplantation |
| Manuscript Type |
Minireviews |
| Article Title |
Application of machine learning in the research progress of post-kidney transplant rejection
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Yun-Peng Guo, Quan Wen, Yu-Yang Wang, Gai Hang and Bo Chen |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Bo Chen, Chief Physician, MD, PhD, Professor, Department of Urinary Surgery, Tongliao People's Hospital, No. 668 Horqin Street, Horqin District, Tongliao 028000, Inner Mongolia Autonomous Region, China. chenmuxin@126.com |
| Key Words |
Machine learning; Kidney transplant; Rejection; Predictive models; Biomarkers; Pathological image analysis; Immune cell infiltration; Precision medicine |
| Core Tip |
Recent advances in machine learning (ML) have opened new avenues for the early prediction and precise diagnosis of rejection in kidney transplantation. ML techniques can analyze large, complex datasets to identify patterns and correlations that may not be readily apparent through conventional analytical methods. By leveraging diverse data sources, including clinical, laboratory, and imaging data, ML models can provide more accurate risk assessments and facilitate timely interventions to mitigate the risk of rejection. |
| Publish Date |
2026-01-14 08:39 |
| Citation |
Guo YP, Wen Q, Wang YY, Hang G, Chen B. Application of machine learning in the research progress of post-kidney transplant rejection. World J Transplant 2026; 16(1): 114000 |
| URL |
https://www.wjgnet.com/2220-3230/full/v16/i1/114000.htm |
| DOI |
https://dx.doi.org/10.5500/wjt.v16.i1.114000 |
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