A. Takigami
Impact in
- Health Informatics top 5%
- Rehabilitation top 5%
- Stroke Rehabilitation and Recovery
Papers in
-
- Acute Myocardial Infarction Research 2
-
- Cardiac Imaging and Diagnostics 3
- Co-authors
- Solaiman Shokur (2 shared papers)Ana R. C. Donati (1 shared paper)Renan C. Moioli (2 shared papers)Simone Gallo (1 shared paper)Gordon Cheng (2 shared papers)Fabrício Lima Brasil (2 shared papers)Hannes Bleuler (1 shared paper)Sanjay S. Joshi (1 shared paper)
- Journals
- Radiology Cardiothoracic Imaging (2 papers)Journal of Clinical Oncology (1 paper)Radiology Artificial Intelligence (1 paper)Scientific Reports (1 paper)Journal of cardiovascular computed tomography (1 paper)
- Partner nations
- United StatesGermanySwitzerland
In The Last Decade
A. Takigami
6 papers receiving 422 citations
A. Takigami's Hit Papers
Peers
Comparison fields: 5 of 61
- Health Informatics 23
- Rehabilitation 64
- Cognitive Neuroscience 171
- Human-Computer Interaction 28
- Cellular and Molecular Neuroscience 87
Countries citing papers authored by A. Takigami
This map shows the geographic impact of A. Takigami'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 A. Takigami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Takigami more than expected).
Fields of papers citing papers by A. Takigami
This network shows the impact of papers produced by A. Takigami. 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 A. Takigami. The network helps show where A. Takigami may publish in the future.
Co-authors
The 25 scholars most cited alongside A. Takigami, 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 | 2016 | 282 | |
| 2 | Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography Hit paper breakdown → | 2023 | 131 |
| 3 | 2022 | 18 | |
| 4 | 2024 | 3 | |
| 5 | 2021 | 1 | |
| 6 | 2020 | 1 | |
| 7 | 2020 | 0 | |
| 8 | The walk again project: Brain-controlled exoskeleton locomotion | 2014 | 0 |
About A. Takigami
A. Takigami is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging, Surgery, Cognitive Neuroscience and Cellular and Molecular Neuroscience, having authored 8 papers that have together received 436 indexed citations. Recurring topics across this work include Cardiac Imaging and Diagnostics (3 papers), EEG and Brain-Computer Interfaces (2 papers), Acute Myocardial Infarction Research (2 papers), Coronary Interventions and Diagnostics (2 papers), Neuroscience and Neural Engineering (1 paper), Muscle activation and electromyography studies (1 paper), Stroke Rehabilitation and Recovery (1 paper) and Infective Endocarditis Diagnosis and Management (1 paper). The work is most often cited by research in Health Informatics (23 citations), Rehabilitation (64 citations), Cognitive Neuroscience (171 citations), Human-Computer Interaction (28 citations) and Cellular and Molecular Neuroscience (87 citations). A. Takigami has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Solaiman Shokur, Ana R. C. Donati, Renan C. Moioli, Simone Gallo, Gordon Cheng, Fabrício Lima Brasil, Hannes Bleuler, Sanjay S. Joshi, Miguel A. L. Nicolelis and Edgard Morya. Their work appears in journals such as Radiology Cardiothoracic Imaging, Journal of Clinical Oncology, Radiology Artificial Intelligence, Scientific Reports and Journal of cardiovascular computed tomography.
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.