Computational psychiatry as a bridge from neuroscience to clinical applications
Impact in
Classified as
- Journal
- Nature Neuroscience
In The Last Decade
doi.org/10.1038/nn.4238 →Countries where authors are citing Computational psychiatry as a bridge from neuroscience to clinical applications
This map shows the geographic impact of Computational psychiatry as a bridge from neuroscience to clinical applications. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Computational psychiatry as a bridge from neuroscience to clinical applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computational psychiatry as a bridge from neuroscience to clinical applications more than expected).
Fields of papers citing Computational psychiatry as a bridge from neuroscience to clinical applications
This network shows the impact of Computational psychiatry as a bridge from neuroscience to clinical applications. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Computational psychiatry as a bridge from neuroscience to clinical applications.
About Computational psychiatry as a bridge from neuroscience to clinical applications
This paper, published in 2016, received 691 indexed citations . Written by Quentin J. M. Huys, Tiago V. Maia and Michael J. Frank covering the research area of Artificial Intelligence, Cognitive Neuroscience and Experimental and Cognitive Psychology. It is primarily cited by scholars working on Cognitive Neuroscience (381 citations), Experimental and Cognitive Psychology (269 citations), Psychiatry and Mental health (95 citations), Clinical Psychology (74 citations) and Artificial Intelligence (61 citations). Published in Nature Neuroscience.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.1038/nn.4238.