Joe Kimura

416 total citations
9 papers, 321 citations indexed

About

Joe Kimura is a scholar working on Geriatrics and Gerontology, General Health Professions and Family Practice. According to data from OpenAlex, Joe Kimura has authored 9 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Geriatrics and Gerontology, 3 papers in General Health Professions and 3 papers in Family Practice. Recurrent topics in Joe Kimura's work include Chronic Disease Management Strategies (3 papers), Frailty in Older Adults (2 papers) and Geriatric Care and Nursing Homes (2 papers). Joe Kimura is often cited by papers focused on Chronic Disease Management Strategies (3 papers), Frailty in Older Adults (2 papers) and Geriatric Care and Nursing Homes (2 papers). Joe Kimura collaborates with scholars based in United States, France and Brazil. Joe Kimura's co-authors include Jonathan P. Weiner, Hadi Kharrazi, Bruce Leff, Cynthia M. Boyd, Richard Marshall, Maryjoan Ladden, Antoinette S. Peters, Gordon T. Moore, Tao Chen and Mark Dredze and has published in prestigious journals such as Clinical Infectious Diseases, Human Molecular Genetics and Journal of the American Geriatrics Society.

In The Last Decade

Joe Kimura

9 papers receiving 307 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Joe Kimura United States 8 85 69 65 58 51 9 321
Marie‐Annick Le Pogam Switzerland 11 68 0.8× 33 0.5× 68 1.0× 39 0.7× 34 0.7× 43 385
Adrian Hapca United Kingdom 9 83 1.0× 36 0.5× 110 1.7× 86 1.5× 54 1.1× 16 382
Adam Hanina United States 4 60 0.7× 44 0.6× 33 0.5× 21 0.4× 47 0.9× 5 377
Sarah Corley United States 8 151 1.8× 100 1.4× 43 0.7× 37 0.6× 48 0.9× 11 412
Joshua W. Devine United States 8 38 0.4× 40 0.6× 57 0.9× 44 0.8× 89 1.7× 23 302
Hanna R. Goldberg Canada 9 99 1.2× 84 1.2× 51 0.8× 27 0.5× 30 0.6× 16 384
Peter Basch United States 8 147 1.7× 110 1.6× 41 0.6× 18 0.3× 67 1.3× 17 453
William W. Quick United States 6 101 1.2× 80 1.2× 117 1.8× 15 0.3× 64 1.3× 8 587
Robert Thombley United States 10 63 0.7× 40 0.6× 58 0.9× 13 0.2× 32 0.6× 26 295
Laura Shafner United States 5 63 0.7× 36 0.5× 44 0.7× 16 0.3× 25 0.5× 7 344

Countries citing papers authored by Joe Kimura

Since Specialization
Citations

This map shows the geographic impact of Joe Kimura's research. 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 Joe Kimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joe Kimura more than expected).

Fields of papers citing papers by Joe Kimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joe Kimura. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joe Kimura. The network helps show where Joe Kimura may publish in the future.

Co-authorship network of co-authors of Joe Kimura

This figure shows the co-authorship network connecting the top 25 collaborators of Joe Kimura. A scholar is included among the top collaborators of Joe Kimura based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joe Kimura. Joe Kimura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Chen, Tao, et al.. (2019). Extraction of Geriatric Syndromes From Electronic Health Record Clinical Notes: Assessment of Statistical Natural Language Processing Methods. JMIR Medical Informatics. 7(1). e13039–e13039. 29 indexed citations
2.
Singh, Karandeep, Niteesh K. Choudhry, Alexis A. Krumme, et al.. (2019). A concept‐wide association study to identify potential risk factors for nonadherence among prevalent users of antihypertensives. Pharmacoepidemiology and Drug Safety. 28(10). 1299–1308. 5 indexed citations
3.
Kan, Hong, Hadi Kharrazi, Bruce Leff, et al.. (2018). Defining and Assessing Geriatric Risk Factors and Associated Health Care Utilization Among Older Adults Using Claims and Electronic Health Records. Medical Care. 56(3). 233–239. 36 indexed citations
4.
Kharrazi, Hadi, et al.. (2018). The Value of Unstructured Electronic Health Record Data in Geriatric Syndrome Case Identification. Journal of the American Geriatrics Society. 66(8). 1499–1507. 87 indexed citations
5.
Franklin, Jessica M., Chandrasekar Gopalakrishnan, Alexis A. Krumme, et al.. (2017). The relative benefits of claims and electronic health record data for predicting medication adherence trajectory. American Heart Journal. 197. 153–162. 24 indexed citations
6.
Peters, Antoinette S., et al.. (2008). A Self-instructional Model to Teach Systems-based Practice and Practice-based Learning and Improvement. Journal of General Internal Medicine. 23(7). 931–936. 39 indexed citations
8.
Gibbs, Laurel, Joe Kimura, N J Troup, et al.. (2002). An Outbreak of Group A Streptococcal Infection among Health Care Workers. Clinical Infectious Diseases. 35(11). 1353–1359. 25 indexed citations
9.
Green, Eric D., Valerie V. Braden, Robert S. Fulton, et al.. (1994). Integration of physical, genetic and cytogenetic maps of human chromosome 7: isolation and analysis of yeast artificial chromosome clones for 117 mapped genetic markers. Human Molecular Genetics. 3(3). 489–501. 47 indexed citations

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.

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