Aaron Long
Impact in
- Health Informatics top 10%
- Materials Chemistry top 10%
- 2D Materials and Applications
- MXene and MAX Phase Materials
- Graphene research and applications
Papers in
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- Digital Radiography and Breast Imaging 2
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- AI in cancer detection 2
- Co-authors
- Luis Balicas (1 shared paper)Ruitao Lv (1 shared paper)Humberto R. Gutiérrez (1 shared paper)Thomas E. Mallouk (1 shared paper)Andrés Castro-Beltrán (1 shared paper)Mauricio Terrones (1 shared paper)Ana Laura Elías (1 shared paper)Néstor Perea‐López (1 shared paper)
- Journals
- Radiology Artificial Intelligence (1 paper)ACS Nano (1 paper)Pediatric Radiology (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2 papers)
- Partner nations
- United StatesMexicoJapan
In The Last Decade
Aaron Long
6 papers receiving 610 citations
Aaron Long's Hit Papers
Peers
Comparison fields: 5 of 67
- Health Informatics 17
- Materials Chemistry 493
- Electrical and Electronic Engineering 264
- Renewable Energy, Sustainability and the Environment 73
- Radiology, Nuclear Medicine and Imaging 51
Countries citing papers authored by Aaron Long
This map shows the geographic impact of Aaron Long'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 Aaron Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron Long more than expected).
Fields of papers citing papers by Aaron Long
This network shows the impact of papers produced by Aaron Long. 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 Aaron Long. The network helps show where Aaron Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Aaron Long, 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 | Controlled Synthesis and Transfer of Large-Area WS2 Sheets: From Single Layer to Few Layers Hit paper breakdown → | 2013 | 537 |
| 2 | 2019 | 42 | |
| 3 | 2020 | 28 | |
| 4 | 2020 | 11 | |
| 5 | 2016 | 3 | |
| 6 | 2017 | 2 |
About Aaron Long
Aaron Long is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence, Media Technology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 6 papers that have together received 623 indexed citations. Recurring topics across this work include Image Processing Techniques and Applications (2 papers), Digital Radiography and Breast Imaging (2 papers), AI in cancer detection (2 papers), Optical Coherence Tomography Applications (1 paper), COVID-19 diagnosis using AI (1 paper), Medical Imaging Techniques and Applications (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Advanced Fluorescence Microscopy Techniques (1 paper). The work is most often cited by research in Health Informatics (17 citations), Materials Chemistry (493 citations), Electrical and Electronic Engineering (264 citations), Renewable Energy, Sustainability and the Environment (73 citations) and Radiology, Nuclear Medicine and Imaging (51 citations). Aaron Long has collaborated with scholars based in United States, Mexico and Japan. Frequent co-authors include Luis Balicas, Ruitao Lv, Humberto R. Gutiérrez, Thomas E. Mallouk, Andrés Castro-Beltrán, Mauricio Terrones, Ana Laura Elías, Néstor Perea‐López, Simin Feng and Morinobu Endo. Their work appears in journals such as Radiology Artificial Intelligence, ACS Nano, Pediatric Radiology and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.