Rob van de Loo

625 total citations
5 papers, 379 citations indexed

About

Rob van de Loo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Oncology. According to data from OpenAlex, Rob van de Loo has authored 5 papers receiving a total of 379 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Oncology. Recurrent topics in Rob van de Loo's work include AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Immune cells in cancer (1 paper). Rob van de Loo is often cited by papers focused on AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Immune cells in cancer (1 paper). Rob van de Loo collaborates with scholars based in Netherlands, Germany and Sweden. Rob van de Loo's co-authors include Geert Litjens, Jeroen van der Laak, Péter Bándi, Peter Bult, Maschenka Balkenhol, Bram van Ginneken, Marcory van Dijk, Paul van Diest, Quirine F. Manson and Rob Vogels and has published in prestigious journals such as Scientific Reports, Journal of Clinical Pathology and The Breast.

In The Last Decade

Rob van de Loo

5 papers receiving 373 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rob van de Loo Netherlands	5	297	212	126	71	49	5	379
Nick Weiss Germany	10	176 0.6×	151 0.7×	104 0.8×	53 0.7×	49 1.0×	16	353
Tianhao Zhao China	7	233 0.8×	163 0.8×	94 0.7×	57 0.8×	56 1.1×	13	349
Monjoy Saha India	10	371 1.2×	269 1.3×	172 1.4×	91 1.3×	73 1.5×	18	559
Mart van Rijthoven Netherlands	7	231 0.8×	169 0.8×	116 0.9×	53 0.7×	76 1.6×	8	338
Ozan Ciga Canada	4	387 1.3×	250 1.2×	193 1.5×	65 0.9×	80 1.6×	4	484
Sahirzeeshan Ali United States	10	259 0.9×	183 0.9×	118 0.9×	57 0.8×	47 1.0×	15	362
Zhaoxuan Ma United States	8	254 0.9×	182 0.9×	84 0.7×	53 0.7×	64 1.3×	9	377
Jesper Molin Sweden	8	242 0.8×	123 0.6×	68 0.5×	63 0.9×	40 0.8×	18	318
Mike Feldman United States	4	267 0.9×	164 0.8×	170 1.3×	41 0.6×	38 0.8×	4	395
Luca L. Weishaupt United States	3	288 1.0×	225 1.1×	85 0.7×	46 0.6×	61 1.2×	6	499

Countries citing papers authored by Rob van de Loo

Since Specialization

Citations

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

Fields of papers citing papers by Rob van de Loo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rob van de Loo. 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 Rob van de Loo. The network helps show where Rob van de Loo may publish in the future.

Co-authorship network of co-authors of Rob van de Loo

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

All Works

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5 of 5 papers shown

1.

Balkenhol, Maschenka, Francesco Ciompi, Żaneta Świderska-Chadaj, et al.. (2021). Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics. The Breast. 56. 78–87. 24 indexed citations

2.

Bulten, Wouter, Péter Bándi, Rob van de Loo, et al.. (2019). Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard. Scientific Reports. 9(1). 864–864. 101 indexed citations

3.

Litjens, Geert, Péter Bándi, Babak Ehteshami Bejnordi, et al.. (2018). 1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset. GigaScience. 7(6). 216 indexed citations

4.

Ooft, Marc Lucas, Rob van de Loo, Cathy B. Moelans, et al.. (2017). Molecular profile of nasopharyngeal carcinoma: analysing tumour suppressor gene promoter hypermethylation by multiplex ligation-dependent probe amplification. Journal of Clinical Pathology. 71(4). 351–359. 9 indexed citations

5.

Bándi, Péter, Rob van de Loo, Francesco Ciompi, et al.. (2017). Comparison of different methods for tissue segmentation in histopathological whole-slide images. 591–595. 29 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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