Jun Maeda
Impact in
- Microbiology top 5%
-
- Lung Cancer Diagnosis and Treatment
- Lung Cancer Treatments and Mutations
- Coronary Artery Anomalies
Papers in ⓘ
-
- Lung Cancer Diagnosis and Treatment 11
- Lung Cancer Treatments and Mutations 9
- Tracheal and airway disorders 6
- Pleural and Pulmonary Diseases 6
- Surgery 22
- Co-authors
- Hiroyuki Yamagishi (25 shared papers)Masahiko Higashiyama (26 shared papers)Ken Kodama (26 shared papers)Deepak Srivastava (5 shared papers)Chihiro Yamagishi (7 shared papers)Jiro Okami (27 shared papers)John McAnally (3 shared papers)Tonghuan Hu (3 shared papers)
- Journals
- Lung Cancer (5 papers)Heart and Vessels (4 papers)Surgery Today (4 papers)Interactive Cardiovascular and Thoracic Surgery (3 papers)Brain Research (3 papers)
- Partner nations
- JapanUnited StatesThailand
In The Last Decade
Jun Maeda
101 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 135
- Microbiology 23
- Pulmonary and Respiratory Medicine 862
- Molecular Biology 1.1k
- Epidemiology 482
- Neurology 112
Countries citing papers authored by Jun Maeda
This map shows the geographic impact of Jun Maeda'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 Jun Maeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Maeda more than expected).
Fields of papers citing papers by Jun Maeda
This network shows the impact of papers produced by Jun Maeda. 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 Jun Maeda. The network helps show where Jun Maeda may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Maeda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 202 | |
| 2 | 2004 | 185 | |
| 3 | 2005 | 129 | |
| 4 | 1981 | 123 | |
| 5 | 2010 | 119 | |
| 6 | 2011 | 115 | |
| 7 | 2010 | 99 | |
| 8 | 2010 | 90 | |
| 9 | 2010 | 80 | |
| 10 | 2007 | 75 | |
| 11 | 2000 | 68 | |
| 12 | 2006 | 66 | |
| 13 | 1998 | 65 | |
| 14 | 2010 | 61 | |
| 15 | 2008 | 55 | |
| 16 | 1987 | 52 | |
| 17 | 2010 | 45 | |
| 18 | 2005 | 43 | |
| 19 | 1982 | 43 | |
| 20 | 2011 | 42 |
About Jun Maeda
Jun Maeda is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Molecular Biology, Epidemiology and Oncology, having authored 111 papers that have together received 2.7k indexed citations. Recurring topics across this work include Congenital Heart Disease Studies (15 papers), Congenital heart defects research (11 papers), Lung Cancer Diagnosis and Treatment (11 papers), Lung Cancer Treatments and Mutations (9 papers), Neuroscience and Neuropharmacology Research (8 papers), Tracheal and airway disorders (6 papers), Pleural and Pulmonary Diseases (6 papers) and Membrane Separation Technologies (5 papers). The work is most often cited by research in Microbiology (23 citations), Pulmonary and Respiratory Medicine (862 citations), Molecular Biology (1.1k citations), Epidemiology (482 citations) and Neurology (112 citations). Jun Maeda has collaborated with scholars based in Japan, United States and Thailand. Frequent co-authors include Hiroyuki Yamagishi, Masahiko Higashiyama, Ken Kodama, Deepak Srivastava, Chihiro Yamagishi, Jiro Okami, John McAnally, Tonghuan Hu, Toshiteru Tokunaga and Tomio Nakayama. Their work appears in journals such as Lung Cancer, Heart and Vessels, Surgery Today, Interactive Cardiovascular and Thoracic Surgery and Brain Research.
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.