Lourdes Durán-López
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Biomedical Engineering
- Pulmonary and Respiratory Medicine
- Co-authors
- Juan P. Dominguez‐MoralesAlejandro Linares-BarrancoSaturnino Vicente-DíazAntonio Félix Conde-MartínDaniel Gutiérrez-GalánÁngel Jiménez-FernándezAntonio Ríos-NavarroFrancisco Luna-Perejón
- Topics
- AI in cancer detection (11 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)Advanced Neural Network Applications (4 papers)
- Journals
- IEEE AccessSensorsNeurocomputing
- Partner nations
- SpainSwitzerlandItaly
In The Last Decade
Lourdes Durán-López
21 papers receiving 279 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 160
- Radiology, Nuclear Medicine and Imaging 143
- Computer Vision and Pattern Recognition 64
- Biomedical Engineering 38
- Pulmonary and Respiratory Medicine 31
Countries citing papers authored by Lourdes Durán-López
This map shows the geographic impact of Lourdes Durán-López'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 Lourdes Durán-López with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lourdes Durán-López more than expected).
Fields of papers citing papers by Lourdes Durán-López
This network shows the impact of papers produced by Lourdes Durán-López. 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 Lourdes Durán-López. The network helps show where Lourdes Durán-López may publish in the future.
Co-authorship network of co-authors of Lourdes Durán-López
This figure shows the co-authorship network connecting the top 25 collaborators of Lourdes Durán-López. A scholar is included among the top collaborators of Lourdes Durán-López 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 Lourdes Durán-López. Lourdes Durán-López is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 3 | |
| 4 | 16 | |
| 5 | 4 | |
| 6 | 8 | |
| 7 | 24 | |
| 8 | 1 | |
| 9 | 17 | |
| 10 | 14 | |
| 11 | 17 | |
| 12 | 2 | |
| 13 | 24 | |
| 14 | 2 | |
| 15 | 60 | |
| 16 | 70 | |
| 17 | 0 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 5 |
About Lourdes Durán-López
Lourdes Durán-López is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics, having authored 23 papers that have together received 288 indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Health Informatics (22 citations), Radiology, Nuclear Medicine and Imaging (143 citations) and Artificial Intelligence (160 citations). Lourdes Durán-López has collaborated with scholars based in Spain, Switzerland and Italy. Frequent co-authors include Juan P. Dominguez‐Morales, Alejandro Linares-Barranco, Saturnino Vicente-Díaz, Antonio Félix Conde-Martín, Daniel Gutiérrez-Galán, Ángel Jiménez-Fernández, Antonio Ríos-Navarro, Francisco Luna-Perejón, José Luis Sevillano and Niccolò Marini. Their work appears in journals such as IEEE Access, Sensors and Neurocomputing.
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.