Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
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doi.org/10.1016/j.bspc.2017.01.012 →Countries where authors are citing Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
This map shows the geographic impact of Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation. 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 Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation more than expected).
Fields of papers citing Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
This network shows the impact of Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation.
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/10.1016/j.bspc.2017.01.012.