Philipp Wesp

936 total citations · 1 hit paper
12 papers, 530 citations indexed

About

Philipp Wesp is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Philipp Wesp has authored 12 papers receiving a total of 530 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Pulmonary and Respiratory Medicine and 3 papers in Oncology. Recurrent topics in Philipp Wesp's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Autopsy Techniques and Outcomes (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). Philipp Wesp is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Autopsy Techniques and Outcomes (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). Philipp Wesp collaborates with scholars based in Germany, United States and Canada. Philipp Wesp's co-authors include Michael Ingrisch, Jens Ricke, Balthasar Schachtner, Bastian O. Sabel, Katharina Jeblick, Andreas Mittermeier, Anna Theresa Stüber, Tobias Weber, Jakob Dexl and Johanna Topalis and has published in prestigious journals such as Radiology, Physics in Medicine and Biology and European Radiology.

In The Last Decade

Philipp Wesp

12 papers receiving 519 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.

ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports

2023 318 citations Katharina Jeblick, Balthasar Schachtner et al. European Radiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Philipp Wesp Germany	7	277	269	175	118	68	12	530
William Shields United Kingdom	9	333 1.2×	293 1.1×	118 0.7×	84 0.7×	71 1.0×	20	563
Felix Busch Germany	15	394 1.4×	363 1.3×	207 1.2×	65 0.6×	106 1.6×	55	813
Sumeet Hindocha United Kingdom	8	178 0.6×	82 0.3×	103 0.6×	86 0.7×	28 0.4×	17	347
Mariko Kawamura Japan	9	231 0.8×	218 0.8×	124 0.7×	49 0.4×	11 0.2×	19	473
Taiki Nozaki Japan	10	242 0.9×	235 0.9×	130 0.7×	52 0.4×	11 0.2×	19	490
Andrew Colucci United States	5	227 0.8×	74 0.3×	84 0.5×	75 0.6×	7 0.1×	8	380
Maya Galperin-Aizenberg United States	13	404 1.5×	68 0.3×	185 1.1×	275 2.3×	11 0.2×	34	704
Shadi Aminololama‐Shakeri United States	12	200 0.7×	33 0.1×	84 0.5×	171 1.4×	13 0.2×	31	389
Farouk Dako United States	10	234 0.8×	119 0.4×	51 0.3×	125 1.1×	5 0.1×	54	492
Reabal Najjar Australia	4	215 0.8×	162 0.6×	80 0.5×	50 0.4×	6 0.1×	6	390

Countries citing papers authored by Philipp Wesp

Since Specialization

Citations

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

Fields of papers citing papers by Philipp Wesp

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philipp Wesp

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

All Works

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12 of 12 papers shown

Fabritius, Matthias P., Michael Winkelmann, Daniel Puhr‐Westerheide, et al.. (2025). Effect of artificial intelligence-aided differentiation of adenomatous and non-adenomatous colorectal polyps at CT colonography on radiologists’ therapy management. European Radiology. 35(7). 4091–4099. 3 indexed citations

Wesp, Philipp, Balthasar Schachtner, Katharina Jeblick, et al.. (2024). Radiological age assessment based on clavicle ossification in CT: enhanced accuracy through deep learning. International Journal of Legal Medicine. 138(4). 1497–1507. 4 indexed citations

Heldring, Nina, et al.. (2024). A probability model for estimating age in young individuals relative to key legal thresholds: 15, 18 or 21-year. International Journal of Legal Medicine. 139(1). 197–217. 3 indexed citations

Wesp, Philipp, Bastian O. Sabel, Andreas Mittermeier, et al.. (2023). Automated localization of the medial clavicular epiphyseal cartilages using an object detection network: a step towards deep learning-based forensic age assessment. International Journal of Legal Medicine. 137(3). 733–742. 3 indexed citations

Jeblick, Katharina, Balthasar Schachtner, Jakob Dexl, et al.. (2023). ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports. European Radiology. 34(5). 2817–2825. 318 indexed citations breakdown →

Mittermeier, Andreas, Paul Reidler, Matthias P. Fabritius, et al.. (2022). End-to-End Deep Learning Approach for Perfusion Data: A Proof-of-Concept Study to Classify Core Volume in Stroke CT. Diagnostics. 12(5). 1142–1142. 5 indexed citations

Wesp, Philipp, Anno Graser, Stefan Maurus, et al.. (2022). Deep learning in CT colonography: differentiating premalignant from benign colorectal polyps. European Radiology. 32(7). 4749–4759. 22 indexed citations

Wesp, Philipp, Anno Graser, Stefan Maurus, et al.. (2021). Machine Learning–based Differentiation of Benign and Premalignant Colorectal Polyps Detected with CT Colonography in an Asymptomatic Screening Population: A Proof-of-Concept Study. Radiology. 299(2). 326–335. 37 indexed citations

Rueckel, Johannes, Christian Huemmer, Andreas Fieselmann, et al.. (2021). Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training. European Radiology. 31(10). 7888–7900. 22 indexed citations

10.

Rueckel, Johannes, Balthasar Schachtner, Philipp Wesp, et al.. (2020). Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs. Investigative Radiology. 55(12). 792–798. 32 indexed citations

11.

Dedes, G., Philipp Wesp, R. P. Johnson, et al.. (2019). Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy. Physics in Medicine and Biology. 64(16). 165002–165002. 59 indexed citations

12.

Wesp, Philipp, Simon Rit, Mark Pankuch, et al.. (2019). Prediction of image noise contributions in proton computed tomography and comparison to measurements. Physics in Medicine and Biology. 64(14). 145016–145016. 22 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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