Carly Eckert
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
-
- Artificial Intelligence in Healthcare
Papers in
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- Artificial Intelligence in Healthcare and Education 6
- Co-authors
- Muhammad Aurangzeb Ahmad (8 shared papers)Ankur M. Teredesai (7 shared papers)Kipruto Kirwa (1 shared paper)Sverre Vedal (1 shared paper)Anjum Hajat (1 shared paper)Joel D. Kaufman (1 shared paper)Daniel T. Lammers (2 shared papers)Matthew J. Eckert (2 shared papers)
- Journals
- Surgical Clinics of North America (2 papers)Annals of Emergency Medicine (1 paper)Applied Clinical Informatics (1 paper)Developmental Biology (1 paper)BMJ Evidence-Based Medicine (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Carly Eckert
16 papers receiving 514 citations
Peers
Comparison fields: 5 of 105
- Health Informatics 104
- Health Information Management 76
- Artificial Intelligence 229
- Safety Research 30
- Radiology, Nuclear Medicine and Imaging 66
Countries citing papers authored by Carly Eckert
This map shows the geographic impact of Carly Eckert'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 Carly Eckert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carly Eckert more than expected).
Fields of papers citing papers by Carly Eckert
This network shows the impact of papers produced by Carly Eckert. 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 Carly Eckert. The network helps show where Carly Eckert may publish in the future.
Co-authors
The 25 scholars most cited alongside Carly Eckert, 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 | 2018 | 357 | |
| 2 | 2020 | 56 | |
| 3 | 2021 | 28 | |
| 4 | 2018 | 19 | |
| 5 | 2021 | 14 | |
| 6 | 2021 | 13 | |
| 7 | 2019 | 12 | |
| 8 | 2019 | 10 | |
| 9 | 2015 | 6 | |
| 10 | 2024 | 5 | |
| 11 | 2023 | 5 | |
| 12 | 2018 | 4 | |
| 13 | 2021 | 4 | |
| 14 | 2018 | 3 | |
| 15 | 2023 | 3 | |
| 16 | The Challenge of Imputation in Explainable Artificial Intelligence Models | 2019 | 1 |
| 17 | Evolution of insect segmentation. | 1999 | 1 |
About Carly Eckert
Carly Eckert is a scholar working on Health Informatics, Health Information Management, Artificial Intelligence, Safety Research and Occupational Therapy, having authored 17 papers that have together received 541 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (6 papers), Machine Learning in Healthcare (5 papers), Explainable Artificial Intelligence (XAI) (4 papers), Ethics and Social Impacts of AI (2 papers), Healthcare cost, quality, practices (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Automotive and Human Injury Biomechanics (1 paper) and Insect-Plant Interactions and Control (1 paper). The work is most often cited by research in Health Informatics (104 citations), Health Information Management (76 citations), Artificial Intelligence (229 citations), Safety Research (30 citations) and Radiology, Nuclear Medicine and Imaging (66 citations). Carly Eckert has collaborated with scholars based in United States and Japan. Frequent co-authors include Muhammad Aurangzeb Ahmad, Ankur M. Teredesai, Kipruto Kirwa, Sverre Vedal, Anjum Hajat, Joel D. Kaufman, Daniel T. Lammers, Matthew J. Eckert, Vikas Kumar and Jason Ray Bingham. Their work appears in journals such as Surgical Clinics of North America, Annals of Emergency Medicine, Applied Clinical Informatics, Developmental Biology and BMJ Evidence-Based Medicine.
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.