Inga Strümke

2.0k total citations · 1 hit paper
35 papers, 892 citations indexed

About

Inga Strümke is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Inga Strümke has authored 35 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Inga Strümke's work include Explainable Artificial Intelligence (XAI) (15 papers), Adversarial Robustness in Machine Learning (4 papers) and Reinforcement Learning in Robotics (4 papers). Inga Strümke is often cited by papers focused on Explainable Artificial Intelligence (XAI) (15 papers), Adversarial Robustness in Machine Learning (4 papers) and Reinforcement Learning in Robotics (4 papers). Inga Strümke collaborates with scholars based in Norway, United States and Germany. Inga Strümke's co-authors include Michael A. Riegler, Pål Halvorsen, Steven A. Hicks, Sravanthi Parasa, Vajira Thambawita, Malek Hammou, Vajira Thambawita, Vince I. Madai, Ayan Paul and Thilo Hagendorff and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and PLoS ONE.

In The Last Decade

Inga Strümke

31 papers receiving 865 citations

Hit 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.

On evaluation metrics for medical applications of artificial intelligence

2022 461 citations Steven A. Hicks, Inga Strümke et al. Scientific Reports profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Inga Strümke Norway	9	271	168	144	102	96	35	892
Vajira Thambawita Norway	10	247 0.9×	183 1.1×	88 0.6×	134 1.3×	91 0.9×	33	792
Silvia Seoni Italy	10	281 1.0×	179 1.1×	155 1.1×	55 0.5×	84 0.9×	33	865
Erico Tjoa Singapore	3	744 2.7×	211 1.3×	214 1.5×	137 1.3×	43 0.4×	3	1.2k
Wenqi Shi United States	15	225 0.8×	340 2.0×	118 0.8×	85 0.8×	41 0.4×	79	954
C. Kambhampati United Kingdom	15	364 1.3×	180 1.1×	190 1.3×	59 0.6×	55 0.6×	73	1.3k
Akhil Vaid United States	16	286 1.1×	202 1.2×	264 1.8×	203 2.0×	311 3.2×	48	1.2k
Zhenxing Xu United States	17	320 1.2×	100 0.6×	81 0.6×	57 0.6×	60 0.6×	51	1.2k
Shinjini Kundu United States	11	173 0.6×	153 0.9×	164 1.1×	50 0.5×	41 0.4×	19	690
Ali Mottaghi United States	4	235 0.9×	229 1.4×	103 0.7×	173 1.7×	23 0.2×	5	743
Steven A. Hicks Norway	18	476 1.8×	355 2.1×	125 0.9×	314 3.1×	96 1.0×	67	1.5k

Countries citing papers authored by Inga Strümke

Since Specialization

Citations

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

Fields of papers citing papers by Inga Strümke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Inga Strümke

This figure shows the co-authorship network connecting the top 25 collaborators of Inga Strümke. A scholar is included among the top collaborators of Inga Strümke 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 Inga Strümke. Inga Strümke 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

Ihlen, Espen A. F., et al.. (2025). Choose your explanation: a comparison of SHAP and Grad-CAM in human activity recognition. Applied Intelligence. 55(17).

Ihlen, Espen A. F., et al.. (2025). Explaining Human Activity Recognition with SHAP: Validating insights with perturbation and quantitative measures. Computers in Biology and Medicine. 188. 109838–109838. 8 indexed citations

Ihlen, Espen A. F., et al.. (2025). Lightweight Neural Architecture Search for Cerebral Palsy Detection. 1–5. 1 indexed citations

Strümke, Inga, et al.. (2024). Information based explanation methods for deep learning agents—with applications on large open-source chess models. Scientific Reports. 14(1). 20174–20174.

Strümke, Inga, et al.. (2024). From Movements to Metrics: Evaluating Explainable AI Methods in Skeleton-Based Human Activity Recognition. Sensors. 24(6). 1940–1940. 8 indexed citations

Lockhart, Sam, Vajira Thambawita, Steven A. Hicks, et al.. (2023). Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis. Diagnostics. 13(14). 2345–2345. 6 indexed citations

Fomin, N., et al.. (2023). Beyond cuts in small signal scenarios. The European Physical Journal C. 83(5). 6 indexed citations

Magnø, Morten Schjerven, Bernd Thiede, Xiangjun Chen, et al.. (2023). Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence. Duo Research Archive (University of Oslo). 9. 204–209. 1 indexed citations

Strümke, Inga, et al.. (2023). Inferring feature importance with uncertainties with application to large genotype data. PLoS Computational Biology. 19(3). e1010963–e1010963. 1 indexed citations

10.

Magnø, Morten Schjerven, Bernd Thiede, Xiangjun Chen, et al.. (2023). Using machine learning model explanations to identify proteins related to severity of meibomian gland dysfunction. Scientific Reports. 13(1). 22946–22946. 3 indexed citations

11.

Amann, Julia, Stig Nikolaj Fasmer Blomberg, Helle Collatz Christensen, et al.. (2022). To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems. SHILAP Revista de lepidopterología. 1(2). e0000016–e0000016. 117 indexed citations

12.

Paul, Ayan, et al.. (2022). Causal connections between socioeconomic disparities and COVID-19 in the USA. Scientific Reports. 12(1). 15827–15827. 8 indexed citations

13.

Hammou, Malek, Cise Midoglu, Steven A. Hicks, et al.. (2022). Huldra. 203–209. 2 indexed citations

14.

Strümke, Inga, et al.. (2022). Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning. 2022 American Control Conference (ACC). 2683–2690. 5 indexed citations

15.

Hicks, Steven A., Inga Strümke, Vajira Thambawita, et al.. (2022). On evaluation metrics for medical applications of artificial intelligence. Scientific Reports. 12(1). 5979–5979. 461 indexed citations breakdown →

16.

Grojean, Christophe, Ayan Paul, Z. Qian, & Inga Strümke. (2022). Lessons on interpretable machine learning from particle physics. Nature Reviews Physics. 4(5). 284–286. 24 indexed citations

17.

Hicks, Steven A., Jonas L. Isaksen, Vajira Thambawita, et al.. (2021). Explaining deep neural networks for knowledge discovery in electrocardiogram analysis. Scientific Reports. 11(1). 10949–10949. 47 indexed citations

18.

Thambawita, Vajira, Steven A. Hicks, Inga Strümke, et al.. (2021). Fr615 IMPACT OF IMAGE RESOLUTION ON CONVOLUTIONAL NEURAL NETWORKS PERFORMANCE IN GASTROINTESTINAL ENDOSCOPY. Gastroenterology. 160(6). S–377. 1 indexed citations

19.

Strümke, Inga, et al.. (2021). Explaining a Deep Reinforcement Learning Docking Agent Using Linear Model Trees with User Adapted Visualization. Journal of Marine Science and Engineering. 9(11). 1178–1178. 13 indexed citations

20.

Thambawita, Vajira, Jonas L. Isaksen, Steven A. Hicks, et al.. (2021). DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine. Scientific Reports. 11(1). 21896–21896. 56 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.

Explore authors with similar magnitude of impact