Gopal Karemore

774 total citations
19 papers, 443 citations indexed

About

Gopal Karemore is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Gopal Karemore has authored 19 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Pulmonary and Respiratory Medicine and 7 papers in Artificial Intelligence. Recurrent topics in Gopal Karemore's work include Digital Radiography and Breast Imaging (8 papers), AI in cancer detection (7 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Gopal Karemore is often cited by papers focused on Digital Radiography and Breast Imaging (8 papers), AI in cancer detection (7 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Gopal Karemore collaborates with scholars based in Denmark, Netherlands and United Kingdom. Gopal Karemore's co-authors include Mads Nielsen, Maj‐Britt Rask, Claudia Lukas, Nico Karssemeijer, Veronica J. Buckle, Fena Ochs, Jill M. Brown, Marko Lampe, Lothar Schermelleh and Hana Polášek-Sedláčková and has published in prestigious journals such as Nature, Nature Communications and Developmental Cell.

In The Last Decade

Gopal Karemore

19 papers receiving 438 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gopal Karemore Denmark 10 263 99 93 90 82 19 443
A Segawa Japan 13 381 1.4× 22 0.2× 115 1.2× 104 1.2× 86 1.0× 25 667
Markus D. Herrmann United States 9 301 1.1× 57 0.6× 51 0.5× 22 0.2× 33 0.4× 26 473
Gerald Fontenay United States 10 288 1.1× 77 0.8× 143 1.5× 55 0.6× 34 0.4× 17 479
Shaolin Mei United States 7 370 1.4× 23 0.2× 176 1.9× 41 0.5× 19 0.2× 11 579
Sunit Maity India 6 681 2.6× 40 0.4× 57 0.6× 17 0.2× 22 0.3× 10 817
Mar Arias-García United Kingdom 7 148 0.6× 28 0.3× 81 0.9× 22 0.2× 80 1.0× 13 337
Irina Klaman Germany 15 630 2.4× 29 0.3× 255 2.7× 80 0.9× 121 1.5× 24 899
Eldo T. Verghese United Kingdom 15 322 1.2× 66 0.7× 198 2.1× 112 1.2× 19 0.2× 29 610
Hung-I Harry Chen United States 10 446 1.7× 40 0.4× 50 0.5× 32 0.4× 27 0.3× 12 662

Countries citing papers authored by Gopal Karemore

Since Specialization
Citations

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

Fields of papers citing papers by Gopal Karemore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gopal Karemore

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

All Works

19 of 19 papers shown
1.
Pedersen, Anna-Kathrine, Gopal Karemore, Vyacheslav Akimov, et al.. (2021). Proteomic investigation of Cbl and Cbl-b in neuroblastoma cell differentiation highlights roles for SHP-2 and CDK16. iScience. 24(4). 102321–102321. 12 indexed citations
2.
Ochs, Fena, Gopal Karemore, Jill M. Brown, et al.. (2019). Stabilization of chromatin topology safeguards genome integrity. Nature. 574(7779). 571–574. 129 indexed citations
3.
Wild, Thomas, Magda Budzowska, Susana Eibes, et al.. (2018). Deletion of APC7 or APC16 Allows Proliferation of Human Cells without the Spindle Assembly Checkpoint. Cell Reports. 25(9). 2317–2328.e5. 8 indexed citations
4.
Karemore, Gopal, Þorkell Guðjόnsson, Maj‐Britt Rask, et al.. (2016). Profiling DNA damage response following mitotic perturbations. Nature Communications. 7(1). 13887–13887. 41 indexed citations
5.
Francavilla, Chiara, Kristoffer Rigbolt, Anna-Kathrine Pedersen, et al.. (2016). Multilayered proteomics reveals molecular switches dictating ligand-dependent EGFR trafficking. Nature Structural & Molecular Biology. 23(6). 608–618. 79 indexed citations
6.
Cayuso, Jordi, Johanna C. Fischer, Gopal Karemore, et al.. (2016). EphrinB1/EphB3b Coordinate Bidirectional Epithelial-Mesenchymal Interactions Controlling Liver Morphogenesis and Laterality. Developmental Cell. 39(3). 316–328. 35 indexed citations
7.
Karemore, Gopal, Mads Nielsen, Nico Karssemeijer, & Sami S. Brandt. (2014). A method to determine the mammographic regions that show early changes due to the development of breast cancer. Physics in Medicine and Biology. 59(22). 6759–6773. 4 indexed citations
8.
Nielsen, Mads, Celine M. Vachon, Christopher G. Scott, et al.. (2014). Mammographic texture resemblance generalizes as an independent risk factor for breast cancer. Breast Cancer Research. 16(2). R37–R37. 33 indexed citations
9.
Azegrouz, Hind, Gopal Karemore, Alberto Torres‐Barrán, et al.. (2013). Cell-Based Fuzzy Metrics Enhance High-Content Screening (HCS) Assay Robustness. SLAS DISCOVERY. 18(10). 1270–1283. 9 indexed citations
10.
Karemore, Gopal. (2012). Computer aided breast cancer risk assessment using shape and texture of breast parenchyma in mammography. 1 indexed citations
11.
Brandt, Sami S., Gopal Karemore, Nico Karssemeijer, & Mads Pagh Nielsen. (2011). An Anatomically Oriented Breast Coordinate System for Mammogram Analysis. IEEE Transactions on Medical Imaging. 30(10). 1841–1851. 19 indexed citations
12.
Nielsen, Mads, Paola C. Pettersen, Peter Alexandersen, et al.. (2010). Breast density changes associated with postmenopausal hormone therapy. Menopause The Journal of The North American Menopause Society. 17(4). 772–778. 6 indexed citations
13.
Karemore, Gopal, Sami S. Brandt, Jon Sporring, & Mads Nielsen. (2010). Anisotropic diffusion tensor applied to temporal mammograms: An application to breast cancer risk assessment. PubMed. 2. 3178–3181. 4 indexed citations
14.
15.
Nielsen, Mads, Gopal Karemore, Marco Loog, et al.. (2010). A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer. Cancer Epidemiology. 35(4). 381–387. 39 indexed citations
16.
Nielsen, Mads, Paola C. Pettersen, Marco Loog, et al.. (2009). Low-dose transdermal estradiol induces breast density and heterogeneity changes comparable to those of raloxifene. Menopause The Journal of The North American Menopause Society. 16(4). 785–791. 9 indexed citations
17.
Karemore, Gopal & Mads Nielsen. (2009). Fractal dimension and lacunarity analysis of mammographic patterns in assessing breast cancer risk related to HRT treated population: a longitudinal and cross-sectional study. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7260. 72602F–72602F. 6 indexed citations
18.
Karemore, Gopal, et al.. (2009). Serum protein profile study of clinical samples using high performance liquid chromatography-laser induced fluorescence: case of cervical and oral cancers. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7182. 71820J–71820J. 2 indexed citations
19.
Karemore, Gopal, Krishna Choudhary, V. K. Unnikrishnan, et al.. (2008). Classification of Laser Induced Fluorescence spectra from normal and malignant tissues using Learning Vector Quantization neural network in bladder cancer diagnosis. Research at the University of Copenhagen (University of Copenhagen). 2. 1–6. 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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