Maria Mavromati

743 citations
25 papers · 444 indexed · h-index 8

Maria Mavromati

19 papers receiving 441 citations

Peers

Maria Mavromati
Comparison fields: 5 of 81
  • Endocrinology, Diabetes and Metabolism 219
  • Endocrine and Autonomic Systems 27
  • Molecular Biology 150
  • Physiology 56
  • Biochemistry 10
Replace Maria Teresa De Síbio with:
Maria Teresa De Síbio Brazil
Hak‐Joong Kim United States
Weiheng Wen China
Cristina Tortoioli Italy
Xiaolong Zhao China
Cuixia Gao China
Monica De Paoli Canada
Zi Guo China
Guang Wang China
Wei Shan China
Maria Mavromati relative to Maria Teresa De Síbio Brazil Maria Teresa De Síbio's profile →
Citations per field
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Maria Teresa De Síbio · 1×
Citations per year

Countries citing papers authored by Maria Mavromati

Since Specialization
Citations

This map shows the geographic impact of Maria Mavromati'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 Maria Mavromati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Mavromati more than expected).

Fields of papers citing papers by Maria Mavromati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maria Mavromati. 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 Maria Mavromati. The network helps show where Maria Mavromati may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Maria Mavromati, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maria Mavromati Line = papers co-authored together Maria Mavromati links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20254
2 20240
3 20242
4 20240
5 20240
6 20237
7 20237
8 20230
9 202310
10 20231
11 20192
12
[Endocrinopathies induced by immune checkpoint inhibitors].
20181
13 201724
14 20170
15 2016114
16 20162
17
[Polycystic ovaries: what's news in 2015?].
20151
18 201231
19 200982
20 200728

About Maria Mavromati

Maria Mavromati is a scholar working on Endocrinology, Diabetes and Metabolism, Reproductive Medicine and Surgery, having authored 25 papers that have together received 444 indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (8 papers), Growth Hormone and Insulin-like Growth Factors (6 papers), Thyroid Cancer Diagnosis and Treatment (4 papers), Thyroid and Parathyroid Surgery (3 papers), Adrenal and Paraganglionic Tumors (3 papers), Thyroid Disorders and Treatments (3 papers), Ovarian function and disorders (2 papers) and Neuroblastoma Research and Treatments (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (219 citations), Endocrine and Autonomic Systems (27 citations) and Molecular Biology (150 citations). Maria Mavromati has collaborated with scholars based in Switzerland, Greece and United States. Frequent co-authors include François R. Jornayvaz, Marc Pusztaszeri, Ildikó Szántó, Philippe Chanson, Anna Makri, George Aggelis, Stylianos Fakas, Jacques Young, Sylvie Brailly‐Tabard and Marie‐Liesse Piketty. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Bioresource Technology and International Journal of Molecular Sciences.

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.

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