Ken Nakagawa
- Pulmonary and Respiratory Medicine top 0.2%
- Oncology top 0.5%
- Molecular Biology top 2%
- Surgery top 1%
- Cancer Research top 0.5%
- Co-authors
- Sakae OkumuraYuichi IshikawaYukitoshi SatohYuki TogashiKengo TakeuchiMototsugu OyaManabu SodaHiroyuki Mano
- Topics
- Lung Cancer Treatments and Mutations (79 papers)Lung Cancer Diagnosis and Treatment (57 papers)Lung Cancer Research Studies (33 papers)
- Partner nations
- JapanIndiaUnited States
In The Last Decade
Ken Nakagawa
305 papers receiving 9.3k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Pulmonary and Respiratory Medicine 5.5k
- Oncology 4.0k
- Molecular Biology 2.7k
- Surgery 1.9k
- Cancer Research 1.8k
Countries citing papers authored by Ken Nakagawa
This map shows the geographic impact of Ken Nakagawa'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 Ken Nakagawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Nakagawa more than expected).
Fields of papers citing papers by Ken Nakagawa
This network shows the impact of papers produced by Ken Nakagawa. 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 Ken Nakagawa. The network helps show where Ken Nakagawa may publish in the future.
Co-authorship network of co-authors of Ken Nakagawa
This figure shows the co-authorship network connecting the top 25 collaborators of Ken Nakagawa. A scholar is included among the top collaborators of Ken Nakagawa 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 Ken Nakagawa. Ken Nakagawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 18 | |
| 3 | Can 18F-FDG PET predict the grade of malignancy in thymic epithelial tumors? An evaluation of only resected tumors | 1 |
| 4 | 43 | |
| 5 | 1 | |
| 6 | 38 | |
| 7 | 77 | |
| 8 | 237 | |
| 9 | KIF5B-ALK, a Novel Fusion Oncokinase Identified by an Immunohistochemistry-based Diagnostic System for ALK-positive Lung Cancerbreakdown → | 557 |
| 10 | 397 | |
| 11 | 22 | |
| 12 | 1 | |
| 13 | 5 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | A randomized trial of intrahepatic infusion chemotherapy for unresectable colorectal liver metastases | 1 |
| 17 | [The influence of smoking on the development of various subtypes of pulmonary carcinoma]. | 2 |
| 18 | 0 | |
| 19 | 1 | |
| 20 | 1 |
About Ken Nakagawa
Ken Nakagawa is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Transplantation, having authored 319 papers that have together received 9.6k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (79 papers), Lung Cancer Diagnosis and Treatment (57 papers) and Lung Cancer Research Studies (33 papers). The work is most often cited by research in Pulmonary and Respiratory Medicine (5.5k citations), Oncology (4.0k citations) and Cancer Research (1.8k citations). Ken Nakagawa has collaborated with scholars based in Japan, India and United States. Frequent co-authors include Sakae Okumura, Yuichi Ishikawa, Yukitoshi Satoh, Yuki Togashi, Kengo Takeuchi, Mototsugu Oya, Manabu Soda, Hiroyuki Mano, Young Lim Choi and Kentaro Inamura. Their work appears in journals such as The Lancet, Nature Medicine and Journal of Clinical Oncology.
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.