Evaluation of PICO as a knowledge representation for clinical questions.
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doi.org/w81507238 →Countries where authors are citing Evaluation of PICO as a knowledge representation for clinical questions.
This map shows the geographic impact of Evaluation of PICO as a knowledge representation for clinical questions.. 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 Evaluation of PICO as a knowledge representation for clinical questions. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Evaluation of PICO as a knowledge representation for clinical questions. more than expected).
Fields of papers citing Evaluation of PICO as a knowledge representation for clinical questions.
This network shows the impact of Evaluation of PICO as a knowledge representation for clinical questions.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Evaluation of PICO as a knowledge representation for clinical questions..
About Evaluation of PICO as a knowledge representation for clinical questions.
This paper, published in 2006, received 628 indexed citations . Written by Xiaoli Huang, Jimmy Lin and Dina Demner‐Fushman covering the research area of Molecular Biology, General Health Professions and Statistics, Probability and Uncertainty. It is primarily cited by scholars working on General Health Professions (97 citations), Public Health, Environmental and Occupational Health (86 citations) and Molecular Biology (78 citations). Published in PubMed.
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/w81507238.