Jasper Linmans

942 total citations
9 papers, 278 citations indexed

About

Jasper Linmans is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jasper Linmans has authored 9 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jasper Linmans's work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Jasper Linmans is often cited by papers focused on AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). Jasper Linmans collaborates with scholars based in Netherlands, Sweden and Germany. Jasper Linmans's co-authors include Martijn Rep, Harold Kistler, Li‐Jun Ma, Sarah M. Schmidt, Peter van Dam, Like Fokkens, Jeroen van der Laak, Geert Litjens, Stefan Elfwing and Bas Beerens and has published in prestigious journals such as Environmental Microbiology, Medical Image Analysis and Laboratory Investigation.

In The Last Decade

Jasper Linmans

9 papers receiving 277 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jasper Linmans Netherlands	7	175	154	61	40	39	9	278
Suyash Bhardwaj India	3	201 1.1×	19 0.1×	46 0.8×	13 0.3×	42 1.1×	9	303
İsmail KUNDURACIOĞLU Türkiye	9	168 1.0×	10 0.1×	53 0.9×	13 0.3×	52 1.3×	12	302
Jialin Zhang China	8	32 0.2×	18 0.1×	37 0.6×	185 4.6×	16 0.4×	16	299
Longxi Zhou Saudi Arabia	7	67 0.4×	11 0.1×	130 2.1×	24 0.6×	150 3.8×	13	328
Xiaoyue Xie China	4	196 1.1×	21 0.1×	11 0.2×	24 0.6×	17 0.4×	12	292
Mehdhar S. A. M. Al-Gaashani China	10	149 0.9×	9 0.1×	73 1.2×	6 0.1×	73 1.9×	19	290
Ananda Mohan Mondal United States	9	28 0.2×	16 0.1×	26 0.4×	166 4.2×	27 0.7×	32	273
Dawid Rymarczyk Poland	5	15 0.1×	16 0.1×	64 1.0×	9 0.2×	31 0.8×	9	161
Ankit Jaiswal India	9	24 0.1×	24 0.2×	20 0.3×	53 1.3×	6 0.2×	32	241
Petr Walczysko Germany	7	28 0.2×	9 0.1×	24 0.4×	68 1.7×	15 0.4×	8	135

Countries citing papers authored by Jasper Linmans

Since Specialization

Citations

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

Fields of papers citing papers by Jasper Linmans

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jasper Linmans

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

All Works

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9 of 9 papers shown

Linmans, Jasper, et al.. (2024). Diffusion models for out-of-distribution detection in digital pathology. Medical Image Analysis. 93. 103088–103088. 13 indexed citations

Linmans, Jasper, Emiel Hoogeboom, Jeroen van der Laak, & Geert Litjens. (2023). The Latent Doctor Model for Modeling Inter-Observer Variability. IEEE Journal of Biomedical and Health Informatics. 28(1). 343–354. 1 indexed citations

Linmans, Jasper, Stefan Elfwing, Jeroen van der Laak, & Geert Litjens. (2022). Predictive uncertainty estimation for out-of-distribution detection in digital pathology. Medical Image Analysis. 83. 102655–102655. 34 indexed citations

Hermsen, Meyke, Valery Volk, Jan Hinrich Bräsen, et al.. (2021). Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning. Laboratory Investigation. 101(8). 970–982. 30 indexed citations

Linmans, Jasper, Jeroen van der Laak, & Geert Litjens. (2020). Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks. 465–478. 10 indexed citations

Linmans, Jasper, Bob van de Velde, & Evangelos Kanoulas. (2018). Improved and Robust Controversy Detection in General Web Pages Using Semantic Approaches under Large Scale Conditions. UvA-DARE (University of Amsterdam). 1647–1650. 2 indexed citations

Winkens, Jim, Jasper Linmans, Bastiaan S. Veeling, Taco Cohen, & Max Welling. (2018). Improved Semantic Segmentation for Histopathology using Rotation Equivariant Convolutional Networks. 9 indexed citations

Beerens, Bas, et al.. (2016). Nuclear dynamics and genetic rearrangement in heterokaryotic colonies of Fusarium oxysporum. Fungal Genetics and Biology. 91. 20–31. 32 indexed citations

Dam, Peter van, Like Fokkens, Sarah M. Schmidt, et al.. (2016). Effector profiles distinguish formae speciales of Fusarium oxysporum. Environmental Microbiology. 18(11). 4087–4102. 147 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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