Statistics versus machine learning
Impact in
Classified as
- Journal
- Nature Methods
In The Last Decade
doi.org/10.1038/nmeth.4642 →Countries where authors are citing Statistics versus machine learning
This map shows the geographic impact of Statistics versus machine learning. 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 Statistics versus machine learning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistics versus machine learning more than expected).
Fields of papers citing Statistics versus machine learning
This network shows the impact of Statistics versus machine learning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Statistics versus machine learning.
About Statistics versus machine learning
This paper, published in 2018, received 985 indexed citations . Written by Danilo Bzdok, Naomi Altman and Martin Krzywinski covering the research area of Artificial Intelligence and Signal Processing. It is primarily cited by scholars working on Artificial Intelligence (124 citations), Molecular Biology (69 citations), Radiology, Nuclear Medicine and Imaging (68 citations), Cognitive Neuroscience (55 citations) and Biomedical Engineering (54 citations). Published in Nature Methods.
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/nmeth.4642.