Germán Corredor

1.6k total citations
57 papers, 908 citations indexed

About

Germán Corredor is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Germán Corredor has authored 57 papers receiving a total of 908 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Oncology, 25 papers in Radiology, Nuclear Medicine and Imaging and 23 papers in Artificial Intelligence. Recurrent topics in Germán Corredor's work include Radiomics and Machine Learning in Medical Imaging (23 papers), AI in cancer detection (23 papers) and Cancer Immunotherapy and Biomarkers (17 papers). Germán Corredor is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (23 papers), AI in cancer detection (23 papers) and Cancer Immunotherapy and Biomarkers (17 papers). Germán Corredor collaborates with scholars based in United States, Colombia and Finland. Germán Corredor's co-authors include Anant Madabhushi, Vamsidhar Velcheti, Pingfu Fu, Michael D. Feldman, Prateek Prasanna, Kaustav Bera, Xiangxue Wang, Eduardo Romero, Priya Velu and Cheng Lu and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Clinical Cancer Research.

In The Last Decade

Germán Corredor

53 papers receiving 901 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Germán Corredor United States	13	524	348	299	293	126	57	908
Xiangxue Wang United States	13	444 0.8×	241 0.7×	339 1.1×	193 0.7×	117 0.9×	31	759
Andreas Kleppe Norway	11	460 0.9×	368 1.1×	356 1.2×	184 0.6×	219 1.7×	22	1.0k
Richard Colling United Kingdom	18	263 0.5×	252 0.7×	318 1.1×	152 0.5×	122 1.0×	47	769
Balázs Ács Sweden	17	461 0.9×	563 1.6×	436 1.5×	167 0.6×	333 2.6×	50	1.2k
Tarjei S. Hveem Norway	12	345 0.7×	332 1.0×	265 0.9×	177 0.6×	211 1.7×	21	841
Dyke Ferber Germany	11	507 1.0×	386 1.1×	579 1.9×	74 0.3×	116 0.9×	23	1.1k
Matahi Moarii France	9	422 0.8×	215 0.6×	434 1.5×	144 0.5×	251 2.0×	12	1.1k
Vincenzo L’Imperio Italy	18	241 0.5×	175 0.5×	245 0.8×	184 0.6×	78 0.6×	103	953
Manohar Pradhan Norway	15	311 0.6×	356 1.0×	240 0.8×	241 0.8×	291 2.3×	50	1.1k
Sara Kochanny United States	16	267 0.5×	341 1.0×	261 0.9×	269 0.9×	205 1.6×	37	1.0k

Countries citing papers authored by Germán Corredor

Since Specialization

Citations

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

Fields of papers citing papers by Germán Corredor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Germán Corredor. 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 Germán Corredor. The network helps show where Germán Corredor may publish in the future.

Co-authorship network of co-authors of Germán Corredor

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

All Works

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20 of 20 papers shown

Corredor, Germán, Elizabeth M. Genega, Omar Y. Mian, et al.. (2025). AI-informed computational pathology classifier predicts outcomes across treatment modalities in muscle-invasive urothelial carcinoma. Cancer Letters. 634. 218059–218059.

Corredor, Germán, et al.. (2025). Artificial intelligence in digital pathology — time for a reality check. Nature Reviews Clinical Oncology. 22(4). 283–291. 8 indexed citations

Oršulić, Sandra, Kailin Yang, Deborah J. Chute, et al.. (2025). Artificial intelligence-based virtual staining platform for identifying tumor-associated macrophages from hematoxylin and eosin-stained images. European Journal of Cancer. 220. 115390–115390. 2 indexed citations

Williams, Kelly T., et al.. (2024). Evaluation of QSAR models for tissue-specific predictive toxicology and risk assessment of military-relevant chemical exposures: A systematic review. Computational Toxicology. 32. 100329–100329. 4 indexed citations

Prasanna, Prateek, et al.. (2024). Data distillation in computational pathology by choosing few representants of the original variance: A use case in ovarian cancer. Expert Systems with Applications. 245. 123028–123028. 2 indexed citations

Corredor, Germán, Jonathan Harris, Can Koyuncu, et al.. (2024). Metrics Derived from Architecture of Tumor-Infiltrating Lymphocytes are Associated with Overall Survival in HPV-Positive Oropharyngeal Squamous Cell Carcinoma Patients: Results from NRG/RTOG 0129 and 0522. International Journal of Radiation Oncology*Biology*Physics. 120(2). S130–S130. 1 indexed citations

Corredor, Germán, Lin Li, Patrick Leo, et al.. (2024). An integrated radiology-pathology machine learning classifier for outcome prediction following radical prostatectomy: Preliminary findings. Heliyon. 10(8). e29602–e29602. 4 indexed citations

Khalighi, Sirvan, Germán Corredor, Pingfu Fu, et al.. (2024). Computational pathology identifies immune-mediated collagen disruption to predict clinical outcomes in gynecologic malignancies. SHILAP Revista de lepidopterología. 4(1). 2–2. 7 indexed citations

Yamada, Koji, et al.. (2024). Evaluating applicability domain of acute toxicity QSAR models for military and industrial chemical risk assessment. Toxicology Letters. 403. 1–8. 1 indexed citations

10.

Li, Haojia, Germán Corredor, Pingfu Fu, et al.. (2024). Association of artificial intelligence–derived collagen disorder architecture (CoDA) features with survival outcome and objective response to immune checkpoint inhibitors in patients with head and neck squamous cell carcinoma.. Journal of Clinical Oncology. 42(16_suppl). 6061–6061. 1 indexed citations

11.

Corredor, Germán, Pingfu Fu, Tuomas Mirtti, et al.. (2024). Image analysis Uncovers associations between immune landscape, collagen structure, and neoadjuvant chemotherapy in high-grade serous ovarian carcinomas. Heliyon. 10(13). e33618–e33618. 2 indexed citations

12.

Koyuncu, Can, Mitchell J. Frederick, Lester D.�R. Thompson, et al.. (2023). Machine learning driven index of tumor multinucleation correlates with survival and suppressed anti-tumor immunity in head and neck squamous cell carcinoma patients. Oral Oncology. 143. 106459–106459. 7 indexed citations

13.

Wang, Zhao, et al.. (2023). Measuring dense false positive regions from segmentation result for whole slide tissue histology image. Journal of Visual Communication and Image Representation. 96. 103929–103929. 1 indexed citations

14.

Castro, Patricia, Germán Corredor, Can Koyuncu, et al.. (2023). Recurrent Oropharyngeal Squamous Cell Carcinomas Maintain Anti-tumor Immunity and Multinucleation Levels Following Completion of Radiation. Head and Neck Pathology. 17(4). 952–960.

15.

Corredor, Germán, et al.. (2023). A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives. Clinical Breast Cancer. 23(8). 800–812. 14 indexed citations

16.

Koyuncu, Can, Paula Toro, Germán Corredor, et al.. (2022). A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study. Oral Oncology. 131. 105942–105942. 12 indexed citations

17.

Lu, Cheng, Can Koyuncu, Germán Corredor, et al.. (2020). Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. Medical Image Analysis. 68. 101903–101903. 41 indexed citations

18.

Khorrami, Mohammadhadi, Prateek Prasanna, Amit Gupta, et al.. (2019). Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer. Cancer Immunology Research. 8(1). 108–119. 200 indexed citations

19.

Corredor, Germán, Xiangxue Wang, Yu Zhou, et al.. (2018). Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non–Small Cell Lung Cancer. Clinical Cancer Research. 25(5). 1526–1534. 162 indexed citations

20.

Whitney, Jon, Germán Corredor, Andrew Janowczyk, et al.. (2018). Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer. BMC Cancer. 18(1). 610–610. 74 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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