Juan P. Casas
- Cardiology and Cardiovascular Medicine top 0.5%
- Epidemiology top 2%
- Surgery top 2%
- Molecular Biology top 10%
- Physiology top 2%
- Co-authors
- Aroon D. HingoraniLeonelo E. BautistaLiam SmeethTina ShahSteve E. HumphriesPablo PerelPankaj SharmaShah Ebrahim
- Topics
- Genetic Associations and Epidemiology (18 papers)Pregnancy and preeclampsia studies (16 papers)Lipoproteins and Cardiovascular Health (13 papers)
- Cited by
- Obstetrics and GynecologyCardiology and Cardiovascular MedicineEndocrinology, Diabetes and Metabolism
- Partner nations
- United KingdomUnited StatesColombia
In The Last Decade
Juan P. Casas
125 papers receiving 8.2k citations
Hit Papers
Peers
Comparison fields: 5 of 171
- Cardiology and Cardiovascular Medicine 2.3k
- Epidemiology 1.2k
- Surgery 1.2k
- Molecular Biology 1.1k
- Physiology 998
Countries citing papers authored by Juan P. Casas
This map shows the geographic impact of Juan P. Casas'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 Juan P. Casas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Juan P. Casas more than expected).
Fields of papers citing papers by Juan P. Casas
This network shows the impact of papers produced by Juan P. Casas. 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 Juan P. Casas. The network helps show where Juan P. Casas may publish in the future.
Co-authorship network of co-authors of Juan P. Casas
This figure shows the co-authorship network connecting the top 25 collaborators of Juan P. Casas. A scholar is included among the top collaborators of Juan P. Casas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Juan P. Casas. Juan P. Casas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 7 | |
| 3 | 21 | |
| 4 | 13 | |
| 5 | 32 | |
| 6 | 13 | |
| 7 | 21 | |
| 8 | 150 | |
| 9 | 3 | |
| 10 | 17 | |
| 11 | 4 | |
| 12 | 24 | |
| 13 | A Random Forest proximity matrix as a new measure for gene annotation | 1 |
| 14 | Using a Random Forest proximity measure for variable importance stratification in genotypic data | 1 |
| 15 | 31 | |
| 16 | 10 | |
| 17 | 25 | |
| 18 | 45 | |
| 19 | 40 | |
| 20 | Bronquiolitis obliterante con nuemonía organizante. Un amplio espectro clínico para una histología similar | 1 |
About Juan P. Casas
Juan P. Casas is a scholar working on Obstetrics and Gynecology, Family Practice and Cardiology and Cardiovascular Medicine, having authored 127 papers that have together received 8.5k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (18 papers), Pregnancy and preeclampsia studies (16 papers) and Lipoproteins and Cardiovascular Health (13 papers). The work is most often cited by research in Obstetrics and Gynecology (860 citations), Cardiology and Cardiovascular Medicine (2.3k citations) and Endocrinology, Diabetes and Metabolism (977 citations). Juan P. Casas has collaborated with scholars based in United Kingdom, United States and Colombia. Frequent co-authors include Aroon D. Hingorani, Leonelo E. Bautista, Liam Smeeth, Tina Shah, Steve E. Humphries, Pablo Perel, Pankaj Sharma, Shah Ebrahim, Patricio López‐Jaramillo and Michael V. Holmes. Their work appears in journals such as New England Journal of Medicine, The Lancet and JAMA.
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.