Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models.
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doi.org/w89771506 →Countries where authors are citing Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models.
This map shows the geographic impact of Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models.. 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 Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. more than expected).
Fields of papers citing Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models.
This network shows the impact of Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models..
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/w89771506.