Meike Nauta

1.3k total citations · 1 hit paper
13 papers, 620 citations indexed

About

Meike Nauta is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics. According to data from OpenAlex, Meike Nauta has authored 13 papers receiving a total of 620 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Health Informatics. Recurrent topics in Meike Nauta's work include Explainable Artificial Intelligence (XAI) (9 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Adversarial Robustness in Machine Learning (3 papers). Meike Nauta is often cited by papers focused on Explainable Artificial Intelligence (XAI) (9 papers), Artificial Intelligence in Healthcare and Education (3 papers) and Adversarial Robustness in Machine Learning (3 papers). Meike Nauta collaborates with scholars based in Netherlands and Germany. Meike Nauta's co-authors include Christin Seifert, Doina Bucur, Maurice van Keulen, Jörg Schlötterer, Shreyasi Pathak, Elisa Nguyen, Jan Trienes, Felix Nensa, Christoph M. Friedrich and Nicole C. Krämer and has published in prestigious journals such as ACM Computing Surveys, European Journal of Radiology and Artificial Intelligence in Medicine.

In The Last Decade

Meike Nauta

13 papers receiving 606 citations

Hit Papers

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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.

From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI

2023 205 citations Meike Nauta, Jan Trienes et al. ACM Computing Surveys profile →

Peers

Countries citing papers authored by Meike Nauta

Since Specialization

Citations

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

Fields of papers citing papers by Meike Nauta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meike Nauta

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

All Works

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13 of 13 papers shown

#	Work	Indexed citations
1	From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI breakdown → 2023 ·ACM Computing Surveys ·Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, (unknown), (unknown), Jörg Schlötterer, Maurice van Keulen, Christin Seifert	205
2	Benchmarking eXplainable AI - A Survey on Available Toolkits and Open Challenges 2023 ·Universitätsbibliographie, Universität Duisburg-Essen ·(unknown), Meike Nauta, (unknown), Shreyasi Pathak, Jörg Schlötterer, Christin Seifert	6
3	Explainable AI in medical imaging: An overview for clinical practitioners – Beyond saliency-based XAI approaches 2023 ·European Journal of Radiology ·(unknown), (unknown), Meike Nauta, Christin Seifert, Nicole C. Krämer, Christoph M. Friedrich, Felix Nensa	88
4	Explainable AI in medical imaging: An overview for clinical practitioners – Saliency-based XAI approaches 2023 ·European Journal of Radiology ·(unknown), (unknown), Meike Nauta, Christin Seifert, Nicole C. Krämer, Christoph M. Friedrich, Felix Nensa	69
5	PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification 2023 ·Meike Nauta, Jörg Schlötterer, Maurice van Keulen, Christin Seifert	44
6	Radiology report generation for proximal femur fractures using deep classification and language generation models 2022 ·Artificial Intelligence in Medicine ·(unknown), Meike Nauta, Marion Koelle, (unknown), (unknown), Johannes H. Hegeman, Christin Seifert	8
7	From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI 2022 ·arXiv (Cornell University) ·Meike Nauta, Jan Trienes, Shreyasi Pathak, Elisa Nguyen, (unknown), (unknown), Jörg Schlötterer, Maurice van Keulen, Christin Seifert	14
8	Uncovering and Correcting Shortcut Learning in Machine Learning Models for Skin Cancer Diagnosis 2021 ·Diagnostics ·Meike Nauta, (unknown), (unknown), Christin Seifert	36
9	Evaluating CNN interpretability on sketch classification 2020 ·University of Twente Research Information ·(unknown), Meike Nauta, Christin Seifert	4
10	Interactive Explanations of Internal Representations of Neural Network Layers: An Exploratory Study on Outcome Prediction of Comatose Patients 2020 ·University of Twente Research Information ·Meike Nauta, Michel J. A. M. van Putten, Marleen C. Tjepkema‐Cloostermans, (unknown), Maurice van Keulen, Christin Seifert	1
11	Causal Discovery with Attention-Based Convolutional Neural Networks 2019 ·Machine Learning and Knowledge Extraction ·Meike Nauta, Doina Bucur, Christin Seifert	138
12	Visualising the Training Process of Convolutional Neural Networks for Non-Experts 2019 ·University of Twente Research Information ·(unknown), (unknown), Meike Nauta, Christin Seifert	2
13	Detecting Hacked Twitter Accounts based on Behavioural Change 2017 ·Research Publications (Maastricht University) ·Meike Nauta, (unknown), Maurice van Keulen	5

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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