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期刊名字 | Nature Machine Intelligence NAT MACH INTELL （此期刊被最新的JCR期刊SCIE收录） LetPub评分 8.7
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声誉 9.9 影响力 8.1 速度 7.4 | |||||||||||||||||||||||||||||||||
| 期刊ISSN | 2522-5839 | 微信扫码收藏此期刊 | ||||||||||||||||||||||||||||||||
| 2022-2023最新影响因子 （数据来源于搜索引擎） | 23.8 点击查看影响因子趋势图 | |||||||||||||||||||||||||||||||||
| 实时影响因子 | 截止2023年6月16日：21.74 | |||||||||||||||||||||||||||||||||
| 2022-2023自引率 | 2.10%点击查看自引率趋势图 | |||||||||||||||||||||||||||||||||
| 五年影响因子 | 27.2 | |||||||||||||||||||||||||||||||||
| h-index | 暂无h-index数据 | |||||||||||||||||||||||||||||||||
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| 期刊简介 | Nature Machine Intelligence will publish high-quality original research and reviews in a wide range of topics in machine learning, robotics and AI. The journal will also explore and discuss the significant impact that these fields are beginning to have on other scientific disciplines as well as many aspects of society and industry. There are countless opportunities where machine intelligence can augment human capabilities and knowledge in fields such as scientific discovery, healthcare, medical diagnostics and safe and sustainable cities, transport and agriculture. At the same time, many important questions on ethical, social and legal issues arise, especially given the fast pace of developments Nature Machine Intelligence will provide a platform to discuss these wide implications — encouraging a cross-disciplinary dialogue — with Comments, News Features, News & Views articles and also Correspondence. | |||||||||||||||||||||||||||||||||
| 期刊官方网站 | https://www.nature.com/natmachintell | |||||||||||||||||||||||||||||||||
| 期刊投稿网址 | https://mts-natmachintell.nature.com/ | |||||||||||||||||||||||||||||||||
| 作者指南网址 | https://www.nature.com/natmachintell/submission-guidelines | |||||||||||||||||||||||||||||||||
| 期刊语言要求 | Language Presenting your work in a well-structured manuscript and in well-written English gives it its best chance for editors and reviewers to understand it and evaluate it fairly. Many researchers find that getting some independent support helps them present their results in the best possible light. 经LetPub语言功底雄厚的美籍native English speaker精心编辑的稿件，不仅能满足Nature Machine Intelligence的语言要求，还能让Nature Machine Intelligence编辑和审稿人得到更好的审稿体验，让稿件最大限度地被Nature Machine Intelligence编辑和审稿人充分理解和公正评估。LetPub的专业SCI论文编辑服务（包括SCI论文英语润色，同行资深专家修改润色，SCI论文专业翻译，SCI论文格式排版，专业学术制图等）帮助作者准备稿件，已助力全球15万+作者顺利发表论文。部分发表范例可查看：服务好评 论文致谢 。 提交文稿 | |||||||||||||||||||||||||||||||||
| 是否OA开放访问 | No | |||||||||||||||||||||||||||||||||
| 通讯方式 | CAMPUS, 4 CRINAN ST, LONDON, ENGLAND, N1 9XW | |||||||||||||||||||||||||||||||||
| 出版商 | SPRINGERNATURE | |||||||||||||||||||||||||||||||||
| 涉及的研究方向 | Multiple- | |||||||||||||||||||||||||||||||||
| 出版国家或地区 | ENGLAND | |||||||||||||||||||||||||||||||||
| 出版语言 | English | |||||||||||||||||||||||||||||||||
| 出版周期 | 12 issues per year | |||||||||||||||||||||||||||||||||
| 出版年份 | 0 | |||||||||||||||||||||||||||||||||
| 年文章数 | 114点击查看年文章数趋势图 | |||||||||||||||||||||||||||||||||
| Gold OA文章占比 | 9.49% | |||||||||||||||||||||||||||||||||
| 研究类文章占比： 文章 ÷（文章 + 综述） | 95.61% | |||||||||||||||||||||||||||||||||
| WOS期刊SCI分区 （ 2022-2023年最新版） | WOS分区等级：1区
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| 中科院《国际期刊预警 名单（试行）》名单 | 2023年01月发布的2023版：不在预警名单中 2021年12月发布的2021版：不在预警名单中 2021年01月发布的2020版：不在预警名单中 | |||||||||||||||||||||||||||||||||
| 中科院SCI期刊分区 （ 2022年12月最新升级版） | 点击查看中科院SCI期刊分区趋势图
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| 中科院SCI期刊分区 （ 2021年12月基础版） |
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| 中科院SCI期刊分区 （ 2021年12月升级版） |
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| 中科院SCI期刊分区 （ 2020年12月旧的升级版） | （没有被旧的JCR升级版收录，仅供参考） | |||||||||||||||||||||||||||||||||
| SCI期刊收录coverage | Science Citation Index Expanded (SCIE) (2020年1月，原SCI撤销合并入SCIE，统称SCIE) Scopus (CiteScore) | |||||||||||||||||||||||||||||||||
| PubMed Central (PMC)链接 | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=2522-5839%5BISSN%5D | |||||||||||||||||||||||||||||||||
| 平均审稿速度 | 网友分享经验： | |||||||||||||||||||||||||||||||||
| 平均录用比例 | 网友分享经验： | |||||||||||||||||||||||||||||||||
| LetPub助力发表 | 经LetPub编辑的稿件平均录用比例是未经润色的稿件的1.5倍，平均审稿时间缩短40%。众多作者在使用LetPub的专业SCI论文编辑服务（包括SCI论文英语润色，同行资深专家修改润色，SCI论文专业翻译，SCI论文格式排版，专业学术制图等）后论文在Nature Machine Intelligence顺利发表。
快看看作者怎么说吧：服务好评 论文致谢 | |||||||||||||||||||||||||||||||||
| 期刊常用信息链接 |
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| 中国学者近期发表的论文 | |
| 1. | Mixed-modality speech recognition and interaction using a wearable artificial throat Author: Yang, Qisheng; Jin, Weiqiu; Zhang, Qihang; Wei, Yuhong; Guo, Zhanfeng; Li, Xiaoshi; Yang, Yi; Luo, Qingquan; Tian, He; Ren, Tian-Ling Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 2, pp. 169-180. DOI: 10.1038/s42256-023-00616-6 DOI |
| 2. | Continuous improvement of self-driving cars using dynamic confidence-aware reinforcement learning Author: Cao, Zhong; Jiang, Kun; Zhou, Weitao; Xu, Shaobing; Peng, Huei; Yang, Diange Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 2, pp. 145-158. DOI: 10.1038/s42256-023-00610-y DOI |
| 3. | Echo state graph neural networks with analogue random resistive memory arrays Author: Wang, Shaocong; Li, Yi; Wang, Dingchen; Zhang, Woyu; Chen, Xi; Dong, Danian; Wang, Songqi; Zhang, Xumeng; Lin, Peng; Gallicchio, Claudio; Xu, Xiaoxin; Liu, Qi; Cheng, Kwang-Ting; Wang, Zhongrui; Shang, Dashan; Liu, Ming Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 2, pp. 104-+. DOI: 10.1038/s42256-023-00609-5 DOI |
| 4. | Stretchable e-skin and transformer enable high-resolution morphological reconstruction for soft robots Author: Hu, Delin; Giorgio-Serchi, Francesco; Zhang, Shiming; Yang, Yunjie Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 3, pp. 261-272. DOI: 10.1038/s42256-023-00622-8 DOI |
| 5. | Parameter-efficient fine-tuning of large-scale pre-trained language models Author: Ding, Ning; Qin, Yujia; Yang, Guang; Wei, Fuchao; Yang, Zonghan; Su, Yusheng; Hu, Shengding; Chen, Yulin; Chan, Chi-Min; Chen, Weize; Yi, Jing; Zhao, Weilin; Wang, Xiaozhi; Liu, Zhiyuan; Zheng, Hai-Tao; Chen, Jianfei; Liu, Yang; Tang, Jie; Li, Juanzi; Sun, Maosong Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 3, pp. 220-+. DOI: 10.1038/s42256-023-00626-4 DOI |
| 6. | Pan-Peptide Meta Learning for T-cell receptor-antigen binding recognition Author: Gao, Yicheng; Gao, Yuli; Fan, Yuxiao; Zhu, Chengyu; Wei, Zhiting; Zhou, Chi; Chuai, Guohui; Chen, Qinchang; Zhang, He; Liu, Qi Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 3, pp. 236-249. DOI: 10.1038/s42256-023-00619-3 DOI |
| 7. | Characterizing the interaction conformation between T-cell receptors and epitopes with deep learning Author: Peng, Xingang; Lei, Yipin; Feng, Peiyuan; Jia, Lemei; Ma, Jianzhu; Zhao, Dan; Zeng, Jianyang Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 4, pp. 395-+. DOI: 10.1038/s42256-023-00634-4 DOI |
| 8. | Multitask joint strategies of self-supervised representation learning on biomedical networks for drug discovery Author: Wang, Xiaoqi; Cheng, Yingjie; Yang, Yaning; Yu, Yue; Li, Fei; Peng, Shaoliang Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 4, pp. 445-456. DOI: 10.1038/s42256-023-00640-6 DOI |
| 9. | Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer Author: Liang, Junhao; Zhang, Weisheng; Yang, Jianghui; Wu, Meilong; Dai, Qionghai; Yin, Hongfang; Xiao, Ying; Kong, Lingjie Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. 5, Issue 4, pp. 408-+. DOI: 10.1038/s42256-023-00635-3 DOI |
| 10. | Linguistically inspired roadmap for building biologically reliable protein language models Author: Vu, Mai Ha; Akbar, Rahmad; Robert, Philippe A.; Swiatczak, Bartlomiej; Sandve, Geir Kjetil; Greiff, Victor; Haug, Dag Trygve Truslew Journal: NATURE MACHINE INTELLIGENCE. 2023; Vol. , Issue , pp. -. DOI: 10.1038/s42256-023-00637-1 DOI |
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