Michael Rivera
Impact in
-
- Thyroid Cancer Diagnosis and Treatment
- Pituitary Gland Disorders and Treatments
- Anatomy top 10%
Papers in
-
- Thyroid Cancer Diagnosis and Treatment 3
- Surgery 1
- Salivary Gland Tumors Diagnosis and Treatment 1
- Co-authors
- Ian Ganly (3 shared papers)Ronald Ghossein (3 shared papers)R. Michael Tuttle (3 shared papers)Tihana Ibrahimpašić (1 shared paper)Iain J. Nixon (1 shared paper)Frank L. Palmer (1 shared paper)Agnese Biagini (1 shared paper)Jatin P. Shah (1 shared paper)
- Journals
- Thyroid (3 papers)Journal of Environmental Science and Health Part B (1 paper)Administration and Policy in Mental Health and Mental Health Services Research (1 paper)Academic Leadership The Online Journal (1 paper)
- Partner nations
- United States
In The Last Decade
Michael Rivera
6 papers receiving 161 citations
Peers
Comparison fields: 5 of 42
- Endocrinology, Diabetes and Metabolism 127
- Anatomy 5
- Pathology and Forensic Medicine 29
- Surgery 56
- Reproductive Medicine 9
Countries citing papers authored by Michael Rivera
This map shows the geographic impact of Michael Rivera'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 Michael Rivera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Rivera more than expected).
Fields of papers citing papers by Michael Rivera
This network shows the impact of papers produced by Michael Rivera. 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 Michael Rivera. The network helps show where Michael Rivera may publish in the future.
Co-authors
The 18 scholars most cited alongside Michael Rivera, 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 | 2013 | 81 | |
| 2 | 2013 | 51 | |
| 3 | 1997 | 25 | |
| 4 | 2018 | 4 | |
| 5 | 2008 | 2 | |
| 6 | 2011 | 2 |
About Michael Rivera
Michael Rivera is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Molecular Biology, Social Psychology and General Health Professions, having authored 6 papers that have together received 165 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (3 papers), Agriculture, Water, and Health (1 paper), Schizophrenia research and treatment (1 paper), Primary Care and Health Outcomes (1 paper), TGF-β signaling in diseases (1 paper), Mental Health Treatment and Access (1 paper), Salivary Gland Tumors Diagnosis and Treatment (1 paper) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (127 citations), Anatomy (5 citations), Pathology and Forensic Medicine (29 citations), Surgery (56 citations) and Reproductive Medicine (9 citations). Michael Rivera has collaborated with scholars based in United States. Frequent co-authors include Ian Ganly, Ronald Ghossein, R. Michael Tuttle, Tihana Ibrahimpašić, Iain J. Nixon, Frank L. Palmer, Agnese Biagini, Jatin P. Shah, Snehal G. Patel and Eyal Robenshtok. Their work appears in journals such as Thyroid, Journal of Environmental Science and Health Part B, Administration and Policy in Mental Health and Mental Health Services Research and Academic Leadership The Online Journal.
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.