Emilly M. Lima

559 citations
15 papers · 304 · h-index 7

Impact in

Papers in

Emilly M. Lima

14 papers receiving 299 citations

Peers

Emilly M. Lima
Comparison fields: 5 of 51
  • Cardiology and Cardiovascular Medicine 151
  • Health Informatics 9
  • Health Information Management 15
  • Nephrology 13
  • Aging 3
Replace Gabriela Paixão with:
Gabriela Paixão Brazil
Nidhi Naik United States
Marcelo Martins Pinto Filho Brazil
Y. Elad United States
Leonardo Bonisson Ribeiro Brazil
Veer Sangha United States
Jennifer Dugan United States
Joseph M. Bumgarner United States
Pak‐Hei Chan Hong Kong
Stephanie Helman United States
Emilly M. Lima relative to Gabriela Paixão Brazil Gabriela Paixão's profile →
Citations per field
00.5×4.3×
Gabriela Paixão · 1×
Citations per year

Countries citing papers authored by Emilly M. Lima

Since Specialization
Citations

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

Fields of papers citing papers by Emilly M. Lima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emilly M. Lima. 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 Emilly M. Lima. The network helps show where Emilly M. Lima may publish in the future.

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2021141
2 201954
3 201930
4 200825
5 202019
6 20199
7 20207
8 20205
9 20234
10 20213
11 20222
12 20212
13 20211
14 20201
15 20211

About Emilly M. Lima

Emilly M. Lima is a scholar working on Cardiology and Cardiovascular Medicine, Epidemiology, Artificial Intelligence, Nephrology and Critical Care and Intensive Care Medicine, having authored 15 papers that have together received 304 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (4 papers), Trypanosoma species research and implications (2 papers), Blood Pressure and Hypertension Studies (2 papers), Machine Learning in Healthcare (2 papers), Parasites and Host Interactions (1 paper), Artificial Intelligence in Healthcare (1 paper), Streptococcal Infections and Treatments (1 paper) and Chronic Kidney Disease and Diabetes (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (151 citations), Health Informatics (9 citations), Health Information Management (15 citations), Nephrology (13 citations) and Aging (3 citations). Emilly M. Lima has collaborated with scholars based in Brazil, United Kingdom and United States. Frequent co-authors include Antônio Luiz Pinho Ribeiro, Derick M. Oliveira, Antônio H. Ribeiro, Paulo R. Gomes, Gabriela Paixão, Éster Cerdeira Sabino, Luana Giatti, Wagner Meira, Sandhi Maria Barreto and Bruce Bartholow Duncan. Their work appears in journals such as Circulation Cardiovascular Imaging, Nature Communications, Journal of Cardiovascular Electrophysiology, Global Heart and PLoS neglected tropical diseases.

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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