Clara I. Sá‎nchez

23.7k total citations · 5 hit papers
108 papers, 14.3k citations indexed

About

Clara I. Sá‎nchez is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Clara I. Sá‎nchez has authored 108 papers receiving a total of 14.3k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Radiology, Nuclear Medicine and Imaging, 40 papers in Ophthalmology and 30 papers in Computer Vision and Pattern Recognition. Recurrent topics in Clara I. Sá‎nchez's work include Retinal Imaging and Analysis (55 papers), Retinal Diseases and Treatments (27 papers) and Glaucoma and retinal disorders (21 papers). Clara I. Sá‎nchez is often cited by papers focused on Retinal Imaging and Analysis (55 papers), Retinal Diseases and Treatments (27 papers) and Glaucoma and retinal disorders (21 papers). Clara I. Sá‎nchez collaborates with scholars based in Netherlands, Spain and United States. Clara I. Sá‎nchez's co-authors include Bram van Ginneken, Geert Litjens, Francesco Ciompi, Arnaud A. A. Setio, Thijs Kooi, Jeroen van der Laak, Mohsen Ghafoorian, Babak Ehteshami Bejnordi, Roberto Hornero and Thomas Theelen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Clara I. Sá‎nchez

100 papers receiving 13.7k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A survey on deep learning in medical image analysis

2017 8.3k citations Geert Litjens, Thijs Kooi et al. Medical Image Analysis profile →
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

2016 863 citations Arnaud A. A. Setio, Francesco Ciompi et al. profile →
Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

2016 722 citations Geert Litjens, Clara I. Sá‎nchez et al. Scientific Reports profile →
Large scale deep learning for computer aided detection of mammographic lesions

2016 676 citations Thijs Kooi, Geert Litjens et al. Medical Image Analysis profile →
Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images

2016 305 citations Mark J. J. P. van Grinsven, Bram van Ginneken et al. profile →

Peers

Clara I. Sá‎nchez

RNMI

CVPR

OPHTH

Daniel L. Rubin United States

Pheng‐Ann Heng Hong Kong

Francesco Ciompi Netherlands

Geert Litjens Netherlands

Hao Chen China

Arnaud A. A. Setio Netherlands

Jeroen van der Laak Netherlands

Jing Qin China

Babak Ehteshami Bejnordi Netherlands

Nima Tajbakhsh United States

Daniel L. Rubin United States

Clara I. Sá‎nchez

8.2k ×1.0

RNMI

5.9k ×1.1

2.2k ×0.6

CVPR

1.7k ×0.9

1.2k ×0.6

OPHTH

Citations per year, relative to Clara I. Sá‎nchez Clara I. Sá‎nchez (= 1×) peers Daniel L. Rubin

Countries citing papers authored by Clara I. Sá‎nchez

Since Specialization

Citations

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

Fields of papers citing papers by Clara I. Sá‎nchez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Clara I. Sá‎nchez. 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 Clara I. Sá‎nchez. The network helps show where Clara I. Sá‎nchez may publish in the future.

Co-authorship network of co-authors of Clara I. Sá‎nchez

This figure shows the co-authorship network connecting the top 25 collaborators of Clara I. Sá‎nchez. A scholar is included among the top collaborators of Clara I. Sá‎nchez 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 Clara I. Sá‎nchez. Clara I. Sá‎nchez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lips, Esther H., Lennart Mulder, Elinor J. Sawyer, et al.. (2025). Deep learning for predicting invasive recurrence of ductal carcinoma in situ: leveraging histopathology images and clinical features. EBioMedicine. 116. 105750–105750. 1 indexed citations

Saitta, Simone, Jos Thannhauser, Clara I. Sá‎nchez, et al.. (2025). Attenuation artifact detection and severity classification in intracoronary OCT using mixed image representations. Pure Amsterdam UMC. 25–25. 1 indexed citations

Calvo, Jesús Rodríguez, Asma Khalil, Alireza A. Shamshirsaz, et al.. (2024). Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome. Medical Image Analysis. 99. 103330–103330. 1 indexed citations

Kho, Eline, et al.. (2024). From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision support. EBioMedicine. 111. 105529–105529. 2 indexed citations

Brawura-Biskupski-Samaha, Robert, Paweł Gutaj, Michał Lipa, et al.. (2023). BabyNet＋＋: Fetal birth weight prediction using biometry multimodal data acquired less than 24 hours before delivery. Computers in Biology and Medicine. 167. 107602–107602. 6 indexed citations

Liefers, Bart, Paul Taylor, Clare Bailey, et al.. (2021). Quantification of Key Retinal Features in Early and Late Age-Related Macular Degeneration Using Deep Learning. American Journal of Ophthalmology. 226. 1–12. 47 indexed citations

Vente, Coen de, et al.. (2021). Making AI Transferable Across OCT Scanners from Different Vendors. Investigative Ophthalmology & Visual Science. 62(8). 2118–2118. 4 indexed citations

González-Gonzalo, Cristina, Eric F. Thee, Bart Liefers, et al.. (2021). Hierarchical curriculum learning for robust automated detection of low-prevalence retinal disease features: application to reticular pseudodrusen. Investigative Ophthalmology & Visual Science. 62(8). 86–86. 1 indexed citations

Meakin, James, Bart Liefers, Cristina González-Gonzalo, et al.. (2019). EyeNED workstation: Development of a multi-modal vendor-independent application for annotation, spatial alignment and analysis of retinal images. Investigative Ophthalmology & Visual Science. 60(9). 6118–6118. 4 indexed citations

10.

Thee, Eric F., et al.. (2019). Automated grading of fundus photographs to identify referable AMD for first-line eye care. Investigative Ophthalmology & Visual Science. 60(9). 1532–1532. 1 indexed citations

11.

Manniesing, Rashindra, Marcel T. H. Oei, Luuk J. Oostveen, et al.. (2017). White Matter and Gray Matter Segmentation in 4D Computed Tomography. Scientific Reports. 7(1). 119–119. 19 indexed citations

12.

Litjens, Geert, Thijs Kooi, Babak Ehteshami Bejnordi, et al.. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis. 42. 60–88. 8341 indexed citations breakdown →

13.

Grinsven, Mark J. J. P. van, Freerk G. Venhuizen, Bram van Ginneken, et al.. (2016). Automatic detection of hemorrhages on color fundus images using deep learning. Investigative Ophthalmology & Visual Science. 57(12). 5966–5966. 4 indexed citations

14.

Venhuizen, Freerk G., Bram van Ginneken, Mark J. J. P. van Grinsven, et al.. (2015). Automated age-related macular degeneration classification in OCT using unsupervised feature learning. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9414. 94141I–94141I. 54 indexed citations

15.

Sá‎nchez, Clara I.. (2010). Lo que esconde tu nombre. Virtual Defense Library (Ministerio de Defensa).

16.

García, María, et al.. (2008). Automatic detection of red lesions in retinal images using a multilayer perceptron neural network. PubMed. 97. 5425–5428. 34 indexed citations

17.

Abásolo, Daniel, Roberto Hornero, Pedro Espino, et al.. (2005). Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy. Clinical Neurophysiology. 116(8). 1826–1834. 205 indexed citations

18.

Sá‎nchez, Clara I.. (2003). El teléfono movil. 160–163. 2 indexed citations

19.

López, María, Clara I. Sá‎nchez, & Roberto Hornero. (2003). Retinal Image Analysis to Detect and Quantify Lesions Associated With Diabetic Retinopathy. Investigative Ophthalmology & Visual Science. 44(13). 3977–3977. 4 indexed citations

20.

Sá‎nchez, Clara I.. (2000). Últimas noticias del paraíso. 1 indexed citations

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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