María Eberg

1.5k citations
37 papers · 1.3k · h-index 15

Impact in

  • Oncology top 10%
    • COVID-19 and healthcare impacts
    • Cancer Immunotherapy and Biomarkers
    • Cancer, Lipids, and Metabolism

Papers in

María Eberg

35 papers receiving 1.2k citations

Peers

María Eberg
Comparison fields: 5 of 81
  • Oncology 287
  • Cancer Research 143
  • Internal Medicine 28
  • Pulmonary and Respiratory Medicine 201
  • Obstetrics and Gynecology 42
Replace Donald J. Lucas with:
Donald J. Lucas United States
Nuriye Özdemir Türkiye
Heath B. Mackley United States
Derek W. Brown United States
Laëtitia Stefani France
Hüseyin Abalı Türkiye
Patrick R. Varley United States
Justin David Blasberg United States
Michael Fuchs Germany
Masakazu Ikenaga Japan
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Citations per field
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Citations per year

Countries citing papers authored by María Eberg

Since Specialization
Citations

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

Fields of papers citing papers by María Eberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside María Eberg, 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 María Eberg Line = papers co-authored together María Eberg links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013566
2 2020126
3 201792
4 202267
5 201753
6 201531
7 201529
8 201426
9 201624
10 201824
11 201822
12 201620
13 201719
14 201618
15 201417
16 201814
17 201712
18 201610
19 201910
20 202210

About María Eberg

María Eberg is a scholar working on Statistics and Probability, Oncology, Cardiology and Cardiovascular Medicine, Public Health, Environmental and Occupational Health and Pathology and Forensic Medicine, having authored 37 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (4 papers), Clinical practice guidelines implementation (3 papers), Acute Myocardial Infarction Research (3 papers), Lymphoma Diagnosis and Treatment (3 papers), Smoking Behavior and Cessation (2 papers), Atrial Fibrillation Management and Outcomes (2 papers), Colorectal Cancer Surgical Treatments (2 papers) and Statistical Methods in Epidemiology (2 papers). The work is most often cited by research in Oncology (287 citations), Cancer Research (143 citations), Internal Medicine (28 citations), Pulmonary and Respiratory Medicine (201 citations) and Obstetrics and Gynecology (42 citations). María Eberg has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Laurent Azoulay, Serge Benayoun, Samy Suissa, Gerald Batist, Armen Garo Aprikian, Oriana Hoi Yun Yu, Kristian B. Filion, Mark Jeffrey Eisenberg, Robert William Platt and Harindra Channa Wijeysundera. Their work appears in journals such as Circulation Cardiovascular Quality and Outcomes, Epidemiology, Digestive and Liver Disease, The American Journal of Cardiology and Pharmacoepidemiology and Drug Safety.

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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