Takeshi Mori
- Microbiology top 5%
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- Lung Cancer Diagnosis and Treatment 40
- Lung Cancer Treatments and Mutations 29
- Medical Imaging and Pathology Studies 10
- Pleural and Pulmonary Diseases 10
- Oncology top 5%
- Infectious Diseases top 5%
- Otorhinolaryngology top 5%
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- Advanced Data Compression Techniques 15
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- Myasthenia Gravis and Thymoma 10
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- Video Coding and Compression Technologies 9
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- Radiomics and Machine Learning in Medical Imaging 9
- Co-authors
- Hiroaki NomoriKoei IkedaKentaro YoshimotoKoichi KawanakaHironori KobayashiYasuomi OhbaKenji ShiraishiKazunori Iwatani
- Journals
- The Lancet (2 papers)Journal of Clinical Oncology (1 paper)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Takeshi Mori
143 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 131
- Microbiology 31
- Pulmonary and Respiratory Medicine 1.3k
- Oncology 621
- Infectious Diseases 421
- Otorhinolaryngology 79
Countries citing papers authored by Takeshi Mori
This map shows the geographic impact of Takeshi Mori'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 Takeshi Mori with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Mori more than expected).
Fields of papers citing papers by Takeshi Mori
This network shows the impact of papers produced by Takeshi Mori. 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 Takeshi Mori. The network helps show where Takeshi Mori may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takeshi Mori, 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 | 2025 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2022 | 22 | |
| 4 | 2022 | 0 | |
| 5 | 2021 | 3 | |
| 6 | Speaker Age Estimation Using Age-Dependent Insensitive Loss | 2020 | 4 |
| 7 | 2020 | 0 | |
| 8 | 2018 | 28 | |
| 9 | 2017 | 4 | |
| 10 | 2017 | 68 | |
| 11 | 2015 | 8 | |
| 12 | 2013 | 10 | |
| 13 | 2011 | 33 | |
| 14 | 2010 | 28 | |
| 15 | 2008 | 2 | |
| 16 | G.711.1: A wideband extension to ITU-T G.711 | 2008 | 9 |
| 17 | 2008 | 22 | |
| 18 | 2006 | 36 | |
| 19 | A real-time PHS music delivery system | 1998 | 0 |
| 20 | 1997 | 20 |
About Takeshi Mori
Takeshi Mori is a scholar working on Microbiology, Pulmonary and Respiratory Medicine and Oncology, having authored 154 papers that have together received 2.9k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (40 papers), Lung Cancer Treatments and Mutations (29 papers), Advanced Data Compression Techniques (15 papers), Medical Imaging and Pathology Studies (10 papers), Myasthenia Gravis and Thymoma (10 papers), Pleural and Pulmonary Diseases (10 papers), Video Coding and Compression Technologies (9 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). The work is most often cited by research in Microbiology (31 citations), Pulmonary and Respiratory Medicine (1.3k citations) and Oncology (621 citations). Takeshi Mori has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Hiroaki Nomori, Koei Ikeda, Kentaro Yoshimoto, Koichi Kawanaka, Hironori Kobayashi, Yasuomi Ohba, Kenji Shiraishi, Kazunori Iwatani, Hidekatsu Shibata and Shinya Shiraishi. Their work appears in journals such as The Lancet, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.