• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Correction: Machine learning approach yields epigenetic biomarkers of food allergy: A novel 13-gene signature to diagnose clinical reactivity.更正:机器学习方法产生食物过敏的表观遗传生物标志物:一种用于诊断临床反应性的新型13基因特征。
PLoS One. 2019 Jul 24;14(7):e0220470. doi: 10.1371/journal.pone.0220470. eCollection 2019.
2
Correction: Biomarkers of erosive arthritis in systemic lupus erythematosus: Application of machine learning models.更正:系统性红斑狼疮中侵蚀性关节炎的生物标志物:机器学习模型的应用
PLoS One. 2019 Jan 30;14(1):e0211791. doi: 10.1371/journal.pone.0211791. eCollection 2019.
3
Correction: Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study.更正:使用内在基因组特征的机器学习对新型病原体进行快速分类:COVID-19案例研究
PLoS One. 2021 Jan 27;16(1):e0246465. doi: 10.1371/journal.pone.0246465. eCollection 2021.
4
Correction: Designing machine learning workflows with an application to topological data analysis.更正:设计机器学习工作流程及其在拓扑数据分析中的应用
PLoS One. 2020 Feb 26;15(2):e0229821. doi: 10.1371/journal.pone.0229821. eCollection 2020.
5
Correction: Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning.更正:利用数据挖掘和机器学习改进基于卫星自动识别系统的捕鱼模式检测
PLoS One. 2016 Sep 22;11(9):e0163760. doi: 10.1371/journal.pone.0163760. eCollection 2016.
6
Correction: The path to international medals: A supervised machine learning approach to explore the impact of coach-led sport-specific and non-specific practice.更正:通往国际奖牌之路:一种监督式机器学习方法,用于探索教练主导的特定运动和非特定运动练习的影响。
PLoS One. 2020 Dec 18;15(12):e0244509. doi: 10.1371/journal.pone.0244509. eCollection 2020.
7
Correction: Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity.更正:使用计算机视觉和机器学习对面部积极和消极情绪强度进行编码自动化。
PLoS One. 2019 Mar 7;14(3):e0213756. doi: 10.1371/journal.pone.0213756. eCollection 2019.
8
Correction: Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.更正:结合机器学习与自然语言处理对化学品气味特征进行预测建模。
PLoS One. 2018 Dec 5;13(12):e0208962. doi: 10.1371/journal.pone.0208962. eCollection 2018.
9
Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.更正:一种预测川崎病患者静脉注射免疫球蛋白抵抗性的机器学习方法:一项基于中国东南部人群的研究。
PLoS One. 2021 Jun 21;16(6):e0253675. doi: 10.1371/journal.pone.0253675. eCollection 2021.
10
Correction: Comparison of risk models for mortality and cardiovascular events between machine learning and conventional logistic regression analysis.更正:机器学习与传统逻辑回归分析在死亡率和心血管事件风险模型方面的比较
PLoS One. 2019 Oct 10;14(10):e0223931. doi: 10.1371/journal.pone.0223931. eCollection 2019.

本文引用的文献

1
Machine learning approach yields epigenetic biomarkers of food allergy: A novel 13-gene signature to diagnose clinical reactivity.机器学习方法生成食物过敏的表观遗传生物标志物:一种用于诊断临床反应性的新的 13 基因特征。
PLoS One. 2019 Jun 19;14(6):e0218253. doi: 10.1371/journal.pone.0218253. eCollection 2019.

更正:机器学习方法产生食物过敏的表观遗传生物标志物:一种用于诊断临床反应性的新型13基因特征。

Correction: Machine learning approach yields epigenetic biomarkers of food allergy: A novel 13-gene signature to diagnose clinical reactivity.

出版信息

PLoS One. 2019 Jul 24;14(7):e0220470. doi: 10.1371/journal.pone.0220470. eCollection 2019.

DOI:10.1371/journal.pone.0220470
PMID:31339952
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6655739/
Abstract

[This corrects the article DOI: 10.1371/journal.pone.0218253.].

摘要

[本文更正了文章的数字对象标识符:10.1371/journal.pone.0218253。]