Makoto Shiga
- Surgery top 10%
- Anesthesiology and Pain Medicine top 0.5%
- Developmental Neuroscience top 2%
- Pulmonary and Respiratory Medicine top 10%
- Critical Care and Intensive Care Medicine top 2%
- Co-authors
- Kahoru NishinaKatsuya MikawaHidefumi ObaraNobuhiro MaekawaHirohiko AkamatsuYukie NiwaYumiko TakaoYozo Hori
- Topics
- Anesthesia and Sedative Agents (17 papers)Respiratory Support and Mechanisms (10 papers)Anesthesia and Pain Management (9 papers)
- Cited by
- Anesthesiology and Pain MedicineDevelopmental NeuroscienceCritical Care and Intensive Care Medicine
In The Last Decade
Makoto Shiga
44 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 95
- Surgery 490
- Anesthesiology and Pain Medicine 485
- Developmental Neuroscience 297
- Pulmonary and Respiratory Medicine 292
- Critical Care and Intensive Care Medicine 248
Countries citing papers authored by Makoto Shiga
This map shows the geographic impact of Makoto Shiga'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 Makoto Shiga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Makoto Shiga more than expected).
Fields of papers citing papers by Makoto Shiga
This network shows the impact of papers produced by Makoto Shiga. 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 Makoto Shiga. The network helps show where Makoto Shiga may publish in the future.
Co-authorship network of co-authors of Makoto Shiga
This figure shows the co-authorship network connecting the top 25 collaborators of Makoto Shiga. A scholar is included among the top collaborators of Makoto Shiga 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 Makoto Shiga. Makoto Shiga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 6 | |
| 4 | 51 | |
| 5 | 28 | |
| 6 | 11 | |
| 7 | 32 | |
| 8 | 11 | |
| 9 | 31 | |
| 10 | 61 | |
| 11 | 60 | |
| 12 | 79 | |
| 13 | 35 | |
| 14 | 84 | |
| 15 | 22 | |
| 16 | 65 | |
| 17 | 25 | |
| 18 | 10 | |
| 19 | 55 | |
| 20 | 37 |
About Makoto Shiga
Makoto Shiga is a scholar working on Anesthesiology and Pain Medicine, Developmental Neuroscience and Critical Care and Intensive Care Medicine, having authored 45 papers that have together received 1.5k indexed citations. Recurring topics across this work include Anesthesia and Sedative Agents (17 papers), Respiratory Support and Mechanisms (10 papers) and Anesthesia and Pain Management (9 papers). The work is most often cited by research in Anesthesiology and Pain Medicine (485 citations), Developmental Neuroscience (297 citations) and Critical Care and Intensive Care Medicine (248 citations). Makoto Shiga has collaborated with scholars based in Japan, Croatia and Mexico. Frequent co-authors include Kahoru Nishina, Katsuya Mikawa, Hidefumi Obara, Nobuhiro Maekawa, Hirohiko Akamatsu, Yukie Niwa, Yumiko Takao, Yozo Hori, Kenji Kuwabara and Takashi Ono. Their work appears in journals such as American Journal of Respiratory and Critical Care Medicine, Critical Care Medicine and Anesthesiology.
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.