Friederike Jungmann

1.5k total citations · 2 hit papers
15 papers, 648 citations indexed

About

Friederike Jungmann is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Artificial Intelligence. According to data from OpenAlex, Friederike Jungmann has authored 15 papers receiving a total of 648 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Oncology and 6 papers in Artificial Intelligence. Recurrent topics in Friederike Jungmann's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Pancreatic and Hepatic Oncology Research (5 papers) and Artificial Intelligence in Healthcare and Education (4 papers). Friederike Jungmann is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Pancreatic and Hepatic Oncology Research (5 papers) and Artificial Intelligence in Healthcare and Education (4 papers). Friederike Jungmann collaborates with scholars based in Germany, United Kingdom and Canada. Friederike Jungmann's co-authors include Georgios Kaissis, Rickmer Braren, Marcus R. Makowski, Daniel Rueckert, Jason Mancuso, M. Steinborn, Jakob Vielhauer, Jonathan Passerat‐Palmbach, Andrew Trask and Robbie Holland and has published in prestigious journals such as Nature Medicine, PLoS ONE and Radiology.

In The Last Decade

Friederike Jungmann

14 papers receiving 634 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.

End-to-end privacy preserving deep learning on multi-institutional medical imaging

2021 255 citations Georgios Kaissis, Alexander Ziller et al. Nature Machine Intelligence profile →
Evaluation and mitigation of the limitations of large language models in clinical decision-making

2024 200 citations Paul Hager, Friederike Jungmann et al. Nature Medicine profile →

Peers

Countries citing papers authored by Friederike Jungmann

Since Specialization

Citations

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

Fields of papers citing papers by Friederike Jungmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Friederike Jungmann

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

All Works

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15 of 15 papers shown

#	Work	Indexed citations
1	Automated CT Measurement of Total Kidney Volume for Predicting Renal Function Decline after ¹⁷⁷Lu Prostate-specific Membrane Antigen–I&T Radioligand Therapy 2025 ·Radiology ·(unknown), Friederike Jungmann, (unknown), Georgios Kaissis, (unknown), Robert Tauber, Christoph Schmaderer, Isabel Rauscher, Bernhard Haller, Marcus R. Makowski, Matthias Eiber, Rickmer Braren	1
2	Leveraging large language models for accurate classification of liver lesions from MRI reports 2025 ·Computational and Structural Biotechnology Journal ·(unknown), (unknown), Ulrike Bauer, Friederike Jungmann, Keno K. Bressem, Felix Busch, Marcus R. Makowski, Lisa C. Adams, Florian T. Gassert	2
3	Evaluation and mitigation of the limitations of large language models in clinical decision-making breakdown → 2024 ·Nature Medicine ·Paul Hager, Friederike Jungmann, Robbie Holland, (unknown), (unknown), (unknown), Jakob Vielhauer, Marcus R. Makowski, Rickmer Braren, Georgios Kaissis, Daniel Rueckert	200
4	Spleen Volume Reduction Is a Reliable and Independent Biomarker for Long-Term Risk of Leukopenia Development in Peptide Receptor Radionuclide Therapy 2024 ·Journal of Nuclear Medicine ·(unknown), Friederike Jungmann, (unknown), Patrick Wenzel, (unknown), (unknown), (unknown), Fabian Geisler, Katharina S. Götze, Alexander von Werder, Matthias Eiber, Marcus R. Makowski, Rickmer Braren, Fabian Lohöfer	0
5	Algorithmic transparency and interpretability measures improve radiologists’ performance in BI-RADS 4 classification 2022 ·European Radiology ·Friederike Jungmann, Sebastian Ziegelmayer, (unknown), Stephan Metz, (unknown), (unknown), Marcus R. Makowski, Georgios Kaissis, Rickmer Braren	9
6	Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index 2022 ·mediaTUM (Technical University of Munich) ·Georgios Kaissis, Moritz Knolle, Friederike Jungmann, Alexander Ziller, Dmitrii Usynin, Daniel Rueckert	1
7	End-to-end privacy preserving deep learning on multi-institutional medical imaging breakdown → 2021 ·Nature Machine Intelligence ·Georgios Kaissis, Alexander Ziller, Jonathan Passerat‐Palmbach, Théo Ryffel, Dmitrii Usynin, Andrew Trask, (unknown), Jason Mancuso, Friederike Jungmann, M. Steinborn, Andreas Saleh, Marcus R. Makowski, Daniel Rueckert, Rickmer Braren	255
8	Efficient, high-performance semantic segmentation using multi-scale feature extraction 2021 ·PLoS ONE ·Moritz Knolle, Georgios Kaissis, Friederike Jungmann, Sebastian Ziegelmayer, (unknown), Marcus R. Makowski, Daniel Rueckert, Rickmer Braren	14
9	[18F]FDG PET/MRI enables early chemotherapy response prediction in pancreatic ductal adenocarcinoma 2021 ·EJNMMI Research ·F Harder, Friederike Jungmann, Georgios Kaissis, Fabian Lohöfer, Sebastian Ziegelmayer, (unknown), Michael Quante, (unknown), Roland M. Schmid, İhsan Ekin Demir, Helmut Frieß, Moritz Wildgruber, Jens T. Siveke, Alexander Muckenhuber, Katja Steiger, Wilko Weichert, Isabel Rauscher, Matthias Eiber, Marcus R. Makowski, Rickmer Braren	15
10	Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging 2021 ·Cancers ·Friederike Jungmann, Georgios Kaissis, Sebastian Ziegelmayer, F Harder, (unknown), Hsi-Yu Yen, Katja Steiger, Wilko Weichert, Rebekka Schirren, (unknown), Helmut Friess, Marcus R. Makowski, Rickmer Braren, Fabian Lohöfer	8
11	Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort 2020 ·Journal of Clinical Medicine ·Egon Burian, Friederike Jungmann, Georgios Kaissis, Fabian Lohöfer, Christoph D. Spinner, Tobias Lahmer, Matthias Treiber, Michael Dommasch, Gerhard Schneider, Fabian Geisler, Wolfgang Huber, Ulrike Protzer, Roland M. Schmid, Markus Schwaiger, Marcus R. Makowski, Rickmer Braren	48
12	Multiparametric Modelling of Survival in Pancreatic Ductal Adenocarcinoma Using Clinical, Histomorphological, Genetic and Image-Derived Parameters 2020 ·Journal of Clinical Medicine ·Georgios Kaissis, Friederike Jungmann, Sebastian Ziegelmayer, Fabian Lohöfer, F Harder, Anna Melissa Schlitter, Alexander Muckenhuber, Katja Steiger, Rebekka Schirren, Helmut Frieß, Roland M. Schmid, Wilko Weichert, Marcus R. Makowski, Rickmer Braren	16
13	Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort 2020 ·SSRN Electronic Journal ·Egon Burian, Friederike Jungmann, Georgios Kaissis, Fabian Lohöfer, Christoph D. Spinner, Tobias Lahmer, Matthias Treiber, Michael Dommasch, Gerhard Schneider, Fabian Geisler, Wolfgang Huber, Ulrike Protzer, Roland M. Schmid, Markus Schwaiger, Marcus R. Makowski, Rickmer Braren	2
14	Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma 2020 ·Journal of Clinical Medicine ·Georgios Kaissis, Sebastian Ziegelmayer, Fabian Lohöfer, F Harder, Friederike Jungmann, (unknown), Alexander Muckenhuber, Hsi-Yu Yen, Katja Steiger, Jens T. Siveke, Helmut Friess, Roland M. Schmid, Wilko Weichert, Marcus R. Makowski, Rickmer Braren	36
15	Deep Convolutional Neural Network-Assisted Feature Extraction for Diagnostic Discrimination and Feature Visualization in Pancreatic Ductal Adenocarcinoma (PDAC) versus Autoimmune Pancreatitis (AIP) 2020 ·Journal of Clinical Medicine ·Sebastian Ziegelmayer, Georgios Kaissis, F Harder, Friederike Jungmann, (unknown), Marcus R. Makowski, Rickmer Braren	41

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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