Kōichi Goto
- Oncology top 0.2%
- Lung Cancer Research Studies 136
- Colorectal Cancer Treatments and Studies 68
- Cancer Immunotherapy and Biomarkers 31
- Pulmonary and Respiratory Medicine top 0.1%
- Lung Cancer Treatments and Mutations 289
- Lung Cancer Diagnosis and Treatment 100
- Cancer Research top 0.5%
- Cancer Genomics and Diagnostics 56
- Molecular Biology top 2%
- Cancer therapeutics and mechanisms 34
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- Neuroendocrine Tumor Research Advances 35
- Co-authors
- Kiyotaka YohSeiji NihoGenichiro IshiiShingo MatsumotoYutaka NishiwakiHironobu OhmatsuYuichiro OheTakashi Seto
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Kōichi Goto
475 papers receiving 10.6k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Oncology 6.6k
- Pulmonary and Respiratory Medicine 6.4k
- Cancer Research 1.9k
- Molecular Biology 3.4k
- Pathology and Forensic Medicine 672
Countries citing papers authored by Kōichi Goto
This map shows the geographic impact of Kōichi Goto'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 Kōichi Goto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kōichi Goto more than expected).
Fields of papers citing papers by Kōichi Goto
This network shows the impact of papers produced by Kōichi Goto. 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 Kōichi Goto. The network helps show where Kōichi Goto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kōichi Goto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 3 | |
| 12 | Selpercatinib in Patients With RET Fusion–Positive Non–Small-Cell Lung Cancer: Updated Safety and Efficacy From the Registrational LIBRETTO-001 Phase I/II Trialbreakdown → | 2022 | 119 |
| 13 | 2022 | 6 | |
| 14 | 2021 | 49 | |
| 15 | 2020 | 38 | |
| 16 | 2019 | 55 | |
| 17 | 2018 | 33 | |
| 18 | 2017 | 131 | |
| 19 | 2016 | 139 | |
| 20 | 2014 | 102 |
About Kōichi Goto
Kōichi Goto is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research, having authored 497 papers that have together received 10.8k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (289 papers), Lung Cancer Research Studies (136 papers), Lung Cancer Diagnosis and Treatment (100 papers), Colorectal Cancer Treatments and Studies (68 papers), Cancer Genomics and Diagnostics (56 papers), Neuroendocrine Tumor Research Advances (35 papers), Cancer therapeutics and mechanisms (34 papers) and Cancer Immunotherapy and Biomarkers (31 papers). The work is most often cited by research in Oncology (6.6k citations), Pulmonary and Respiratory Medicine (6.4k citations) and Cancer Research (1.9k citations). Kōichi Goto has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Kiyotaka Yoh, Seiji Niho, Genichiro Ishii, Shingo Matsumoto, Yutaka Nishiwaki, Hironobu Ohmatsu, Yuichiro Ohe, Takashi Seto, Nobuyuki Yamamoto and Makoto Nishio.
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.