Nature Machine Intelligence
Q1 Journal
Open Access
Journal
Country
Switzerland
Western Europe
Subject Area and Category
Computer Science
└
Artificial Intelligence
Q1
└
Computer Networks and Communications
Q1
└
Computer Vision and Pattern Recognition
Q1
Publisher
SJR 2025
6.902
Q1
SJR Score
H-Index
118
Citations / Doc (2yr)
22.28
Total Docs. (latest)
196
Total Citations (3yr)
11,696
Publication type
Journals
ISSN
25225839
Coverage
2019-2026
Journal Rank
#165
Subject Categories
Artificial Intelligence
Q1
Computer Networks and Communications
Q1
Computer Vision and Pattern Recognition
Q1
Human-Computer Interaction
Q1
Software
Q1
Subject Areas
Aims & Scope
Nature Machine Intelligence publishes high-quality original research and reviews in a wide range of topics in machine learning, robotics and AI.
We 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 provides a platform to discuss these wide implications — encouraging a cross-disciplinary dialogue — with Comments, News Features, News & Views articles and also Correspondence.
Like all Nature-branded journals, Nature Machine Intelligence is run by a team of professional editors and dedicated to a fair and rigorous peer-review process, high standards of copy-editing and production, swift publication, and editorial independence.
Abstracting & Indexing
Scopus
Google Scholar
Web of Science
Detailed Metrics
| Total Docs. (latest) | 196 |
| Total Docs. (3 years) | 503 |
| Total Refs. | 11,080 |
| Total Citations (3 years) | 11,696 |
| Citable Docs. (3 years) | 371 |
| Citations / Doc. (2 years) | 22.28 |
| Ref. / Doc. | 56.53 |
| % Female | 28.2% |
Metrics Visualization
Latest year data vs 3-year cumulative figures
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