Anna Siefkas
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Internal Medicine top 10%
- Venous Thromboembolism Diagnosis and Management
Papers in
-
- COVID-19 Clinical Research Studies 3
- SARS-CoV-2 and COVID-19 Research 2
- Health 2
- Health disparities and outcomes 2
- Co-authors
- Ritankar Das (10 shared papers)Gina Barnes (11 shared papers)Jana Hoffman (11 shared papers)Jacob Calvert (10 shared papers)Emily Pellegrini (6 shared papers)Abigail Green‐Saxena (7 shared papers)Hoyt Burdick (6 shared papers)Qingqing Mao (7 shared papers)
- Journals
- Clinical Therapeutics (2 papers)Pancreatology (1 paper)Journal of Foot and Ankle Research (1 paper)Medicine (1 paper)Journal of Applied Gerontology (1 paper)
- Partner nations
- United StatesBelgiumUnited Kingdom
In The Last Decade
Anna Siefkas
16 papers receiving 317 citations
Peers
Comparison fields: 5 of 75
- Health Informatics 36
- Internal Medicine 25
- Health Information Management 32
- Critical Care and Intensive Care Medicine 16
- Radiology, Nuclear Medicine and Imaging 74
Countries citing papers authored by Anna Siefkas
This map shows the geographic impact of Anna Siefkas'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 Anna Siefkas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Siefkas more than expected).
Fields of papers citing papers by Anna Siefkas
This network shows the impact of papers produced by Anna Siefkas. 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 Anna Siefkas. The network helps show where Anna Siefkas may publish in the future.
Co-authors
The 25 scholars most cited alongside Anna Siefkas, 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 | 2020 | 97 | |
| 2 | 2021 | 44 | |
| 3 | 2020 | 35 | |
| 4 | 2021 | 34 | |
| 5 | 2021 | 34 | |
| 6 | 2021 | 28 | |
| 7 | 2021 | 16 | |
| 8 | 2021 | 11 | |
| 9 | 2022 | 9 | |
| 10 | 2021 | 8 | |
| 11 | 2021 | 7 | |
| 12 | 2020 | 6 | |
| 13 | 2022 | 4 | |
| 14 | 2022 | 3 | |
| 15 | Using Machine Learning as a Precision Medicine Approach for Remdesivir and Corticosteroids as COVID-19 Pharmacotherapies | 2021 | 1 |
| 16 | 2023 | 1 | |
| 17 | 2021 | 0 |
About Anna Siefkas
Anna Siefkas is a scholar working on Infectious Diseases, Health, Health Informatics, Epidemiology and Artificial Intelligence, having authored 17 papers that have together received 338 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Health disparities and outcomes (2 papers), COVID-19 diagnosis using AI (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Acute Myeloid Leukemia Research (1 paper), Artificial Intelligence in Healthcare (1 paper) and Venous Thromboembolism Diagnosis and Management (1 paper). The work is most often cited by research in Health Informatics (36 citations), Internal Medicine (25 citations), Health Information Management (32 citations), Critical Care and Intensive Care Medicine (16 citations) and Radiology, Nuclear Medicine and Imaging (74 citations). Anna Siefkas has collaborated with scholars based in United States, Belgium and United Kingdom. Frequent co-authors include Ritankar Das, Gina Barnes, Jana Hoffman, Jacob Calvert, Emily Pellegrini, Abigail Green‐Saxena, Hoyt Burdick, Qingqing Mao, Samson Mataraso and Gregory L. Braden. Their work appears in journals such as Clinical Therapeutics, Pancreatology, Journal of Foot and Ankle Research, Medicine and Journal of Applied Gerontology.
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.