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2023/7/9 13:50:44 | Browse: 255 | 下载: 458
| Publication Name |
世界华人消化杂志 |
| 手稿编号 |
39459 |
| 手稿来源省、自治区或特别行政区 |
安徽省 |
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Received |
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2023-04-20 00:41 |
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Peer-Review Started |
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2023-04-20 00:47 |
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To Make the First Decision |
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Return for Revision |
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2023-05-19 22:26 |
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修回稿 |
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2023-05-25 10:27 |
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Second Decision |
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2023-06-21 14:06 |
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期刊总编辑接受 |
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公司总编辑接受 |
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2023-06-21 20:19 |
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预出版 |
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2023-06-21 20:19 |
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缴纳版面费 |
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Edit the Manuscript by Language Editor |
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排版 |
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2023-07-07 11:26 |
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在线出版 |
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2023-07-08 14:26 |
| ISSN |
1009-3079 (print) and 2219-2859 (online) |
| 开放获取 |
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/ |
| 版权 |
© The Author(s) 2023. 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 |
| 网址 |
http://www.wjgnet.com |
| 专业类型 |
消化内科学 |
| 手稿栏目类型 |
临床研究 |
| 文章标题 |
XGBoost机器学习模型对乙型肝炎肝硬化诊断的应用价值研究
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| 手稿来源 |
自由来稿 |
| 所有作者列表 |
李季, 韩可兴, 沈佳培, 孙伟杰, 高龙, 郜玉峰 |
| 基金项目及其编号 |
| 基金项目名称 |
基金编号 |
| 安徽省自然科学基金 |
2208085MH204 |
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| 通讯作者 |
郜玉峰, 博士, 主任医师, 23000, 安徽省合肥市绩溪路218号, 安徽医科大学第一附属医院感染科. aygyf@ahmu.edu.cn |
| 关键词 |
慢性乙型病毒性肝炎; 肝硬化; 预测模型; XGBoost机器学习模型 |
| 核心内容提要 |
本研究重点探究以慢性乙型肝炎病毒感染患者年龄和临床常见指标构建极限梯度提升机机器学习模型, 为肝硬化的早期管理提供参考依据. |
| 出版日期 |
2023-07-08 14:26 |
| 引文著录 |
李季, 韩可兴, 沈佳培, 孙伟杰, 高龙, 郜玉峰. XGBoost机器学习模型对乙型肝炎肝硬化诊断的应用价值研究. 世界华人消化杂志 2023; 31(13): 544-554 |
| URL |
https://www.wjgnet.com/1009-3079/full/v31/i13/544.htm |
| DOI |
https://dx.doi.org/10.11569/wcjd.v31.i13.544 |
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