Anna Merino
Impact in
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- Digital Imaging for Blood Diseases
- Biophysics top 2%
- Cell Image Analysis Techniques
Papers in
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- Digital Imaging for Blood Diseases 21
- Hematology 12
- Hematopoietic Stem Cell Transplantation 4
- Co-authors
- José Rodellar (22 shared papers)Santiago Alférez (20 shared papers)Andrea Acevedo (12 shared papers)Ángel Molina (19 shared papers)Laura Boldú (12 shared papers)Pilar Arrizabalaga (3 shared papers)Odette Viñas (3 shared papers)Yael Dror (4 shared papers)
- Journals
- Blood (6 papers)British Journal of Haematology (6 papers)Computer Methods and Programs in Biomedicine (4 papers)Journal of Clinical Pathology (4 papers)Transfusion (3 papers)
- Partner nations
- SpainColombiaUnited States
In The Last Decade
Anna Merino
65 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 115
- Computer Vision and Pattern Recognition 778
- Biophysics 161
- Health Informatics 26
- Artificial Intelligence 433
- Radiology, Nuclear Medicine and Imaging 274
Countries citing papers authored by Anna Merino
This map shows the geographic impact of Anna Merino'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 Anna Merino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Merino more than expected).
Fields of papers citing papers by Anna Merino
This network shows the impact of papers produced by Anna Merino. 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 Anna Merino. The network helps show where Anna Merino may publish in the future.
Co-authors
The 25 scholars most cited alongside Anna Merino, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 178 | |
| 2 | 2019 | 145 | |
| 3 | 2021 | 87 | |
| 4 | 2018 | 87 | |
| 5 | 1993 | 82 | |
| 6 | 2018 | 56 | |
| 7 | 2015 | 53 | |
| 8 | 2020 | 50 | |
| 9 | 2019 | 43 | |
| 10 | Granulocyte colony-stimulating factor increases expression of adhesion receptors on endothelial cells through activation of p38 MAPK. | 2004 | 41 |
| 11 | 2021 | 40 | |
| 12 | 2022 | 37 | |
| 13 | 2016 | 37 | |
| 14 | 2014 | 32 | |
| 15 | 2020 | 28 | |
| 16 | 2021 | 26 | |
| 17 | 2013 | 26 | |
| 18 | 2021 | 21 | |
| 19 | 2016 | 21 | |
| 20 | 2009 | 18 |
About Anna Merino
Anna Merino is a scholar working on Computer Vision and Pattern Recognition, Hematology, Physiology, Epidemiology and Genetics, having authored 71 papers that have together received 1.4k indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (21 papers), Clinical Laboratory Practices and Quality Control (8 papers), Hematopoietic Stem Cell Transplantation (4 papers), AI in cancer detection (4 papers), Cell Image Analysis Techniques (4 papers), Neonatal Health and Biochemistry (3 papers), Immunodeficiency and Autoimmune Disorders (3 papers) and Hemoglobinopathies and Related Disorders (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (778 citations), Biophysics (161 citations), Health Informatics (26 citations), Artificial Intelligence (433 citations) and Radiology, Nuclear Medicine and Imaging (274 citations). Anna Merino has collaborated with scholars based in Spain, Colombia and United States. Frequent co-authors include José Rodellar, Santiago Alférez, Andrea Acevedo, Ángel Molina, Laura Boldú, Pilar Arrizabalaga, Odette Viñas, Yael Dror, Malika Benkerrou and MJ Cowan. Their work appears in journals such as Blood, British Journal of Haematology, Computer Methods and Programs in Biomedicine, Journal of Clinical Pathology and Transfusion.
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.