Laura Boldú
Impact in
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- Digital Imaging for Blood Diseases
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- Digital Imaging for Blood Diseases 7
- Genetics 2
- Myeloproliferative Neoplasms: Diagnosis and Treatment 1
- Hemoglobinopathies and Related Disorders 1
- Co-authors
- Anna Merino (12 shared papers)José Rodellar (10 shared papers)Ángel Molina (9 shared papers)Andrea Acevedo (8 shared papers)Santiago Alférez (8 shared papers)Ana Merino (1 shared paper)Anton A. M. Ermens (1 shared paper)Alexandru Vlagea (1 shared paper)
- Journals
- Journal of Clinical Pathology (3 papers)Computers in Biology and Medicine (2 papers)Computer Methods and Programs in Biomedicine (1 paper)American Journal of Clinical Pathology (1 paper)Clinical Chemistry and Laboratory Medicine (CCLM) (1 paper)
- Partner nations
- SpainColombiaNetherlands
In The Last Decade
Laura Boldú
13 papers receiving 484 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 361
- Biophysics 69
- Health Informatics 14
- Artificial Intelligence 223
- Radiology, Nuclear Medicine and Imaging 141
Countries citing papers authored by Laura Boldú
This map shows the geographic impact of Laura Boldú'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 Laura Boldú with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura Boldú more than expected).
Fields of papers citing papers by Laura Boldú
This network shows the impact of papers produced by Laura Boldú. 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 Laura Boldú. The network helps show where Laura Boldú may publish in the future.
Co-authors
The 12 scholars most cited alongside Laura Boldú, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 178 | |
| 2 | 2021 | 87 | |
| 3 | 2018 | 56 | |
| 4 | 2019 | 43 | |
| 5 | 2021 | 40 | |
| 6 | 2020 | 28 | |
| 7 | 2021 | 26 | |
| 8 | 2018 | 12 | |
| 9 | 2020 | 11 | |
| 10 | 2022 | 6 | |
| 11 | 2019 | 3 | |
| 12 | 2022 | 1 | |
| 13 | 2019 | 1 |
About Laura Boldú
Laura Boldú is a scholar working on Computer Vision and Pattern Recognition, Genetics, Artificial Intelligence, Hematology and Infectious Diseases, having authored 13 papers that have together received 492 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (7 papers), AI in cancer detection (2 papers), Acute Myeloid Leukemia Research (1 paper), COVID-19 Clinical Research Studies (1 paper), Myeloproliferative Neoplasms: Diagnosis and Treatment (1 paper), Cancer Genomics and Diagnostics (1 paper), Hemoglobinopathies and Related Disorders (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (361 citations), Biophysics (69 citations), Health Informatics (14 citations), Artificial Intelligence (223 citations) and Radiology, Nuclear Medicine and Imaging (141 citations). Laura Boldú has collaborated with scholars based in Spain, Colombia and Netherlands. Frequent co-authors include Anna Merino, José Rodellar, Ángel Molina, Andrea Acevedo, Santiago Alférez, Ana Merino, Anton A. M. Ermens, Alexandru Vlagea, Natalia Egri and Oriol Sibila. Their work appears in journals such as Journal of Clinical Pathology, Computers in Biology and Medicine, Computer Methods and Programs in Biomedicine, American Journal of Clinical Pathology and Clinical Chemistry and Laboratory Medicine (CCLM).
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.