Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients.
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doi.org/w87611804 →Countries where authors are citing Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients.
This map shows the geographic impact of Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients.. 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 Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients. more than expected).
Fields of papers citing Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients.
This network shows the impact of Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients..
About Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients.
This paper, published in 2000, received 578 indexed citations . Written by Masayoshi Shichiri, Hiroki Kishikawa, Y Ohkubo and Nakayasu Wake covering the research area of Neurology and Ophthalmology. It is primarily cited by scholars working on Endocrinology, Diabetes and Metabolism (464 citations), Molecular Biology (114 citations) and Surgery (72 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/w87611804.