Paul K. Gerke

1.6k total citations · 1 hit paper
8 papers, 979 citations indexed

About

Paul K. Gerke is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications. According to data from OpenAlex, Paul K. Gerke has authored 8 papers receiving a total of 979 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pulmonary and Respiratory Medicine, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Computer Networks and Communications. Recurrent topics in Paul K. Gerke's work include Lung Cancer Diagnosis and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Distributed Control Multi-Agent Systems (2 papers). Paul K. Gerke is often cited by papers focused on Lung Cancer Diagnosis and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Distributed Control Multi-Agent Systems (2 papers). Paul K. Gerke collaborates with scholars based in Netherlands, United States and Italy. Paul K. Gerke's co-authors include Bram van Ginneken, Colin Jacobs, Francesco Ciompi, Arnaud A. A. Setio, Geert Litjens, Matiullah Naqibullah, Mathilde Marie Winkler Wille, Clara I. Sá‎nchez, Sarah J. van Riel and Kaman Chung and has published in prestigious journals such as Radiology, IEEE Transactions on Medical Imaging and Thorax.

In The Last Decade

Paul K. Gerke

8 papers receiving 936 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.

Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

2016 863 citations Arnaud A. A. Setio, Francesco Ciompi et al. IEEE Transactions on Medical Imaging profile →

Peers

Countries citing papers authored by Paul K. Gerke

Since Specialization

Citations

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

Fields of papers citing papers by Paul K. Gerke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul K. Gerke. 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 Paul K. Gerke. The network helps show where Paul K. Gerke may publish in the future.

Co-authorship network of co-authors of Paul K. Gerke

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

All Works

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8 of 8 papers shown

#	Work	Indexed citations
1	Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists 2021 ·Radiology Artificial Intelligence ·Colin Jacobs, Arnaud A. A. Setio, Ernst T. Scholten, Paul K. Gerke, (unknown), Firdaus A. Mohamed Hoesein, Monique Brink, Erik Ranschaert, Pim A. de Jong, Mario Silva, Bram Geurts, Kaman Chung, Steven Schalekamp, Joke Meersschaert, Anand Devaraj, Paul F. Pinsky, Stephen Lam, Bram van Ginneken, Keyvan Farahani	29
2	Brock malignancy risk calculator for pulmonary nodules: validation outside a lung cancer screening population 2018 ·Thorax ·Kaman Chung, Onno M. Mets, Paul K. Gerke, Colin Jacobs, Annemarie M. den Harder, Ernst T. Scholten, Mathias Prokop, Pim A. de Jong, Bram van Ginneken, Cornelia Schaefer‐Prokop	33
3	Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules? 2017 ·Radiology ·Kaman Chung, Colin Jacobs, Ernst T. Scholten, Jin Mo Goo, Helmut Prosch, Nicola Sverzellati, Francesco Ciompi, Onno M. Mets, Paul K. Gerke, Mathias Prokop, Bram van Ginneken, Cornelia Schaefer‐Prokop	43
4	Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks breakdown → 2016 ·IEEE Transactions on Medical Imaging ·Arnaud A. A. Setio, Francesco Ciompi, Geert Litjens, Paul K. Gerke, Colin Jacobs, Sarah J. van Riel, Mathilde Marie Winkler Wille, Matiullah Naqibullah, Clara I. Sá‎nchez, Bram van Ginneken	863
5	Crowdsourcing as a methodology to obtain large and varied robotic data sets 2014 ·Guido de Croon, Paul K. Gerke, I.G. Sprinkhuizen-Kuyper	4
6	Astro Drone: Using crowdsourcing to collect visual data for distance estimation 2013 ·Paul K. Gerke	1
7	BioMAV: bio-inspired intelligence for autonomous flight 2012 ·Research Repository (Delft University of Technology) ·Paul K. Gerke, (unknown), Stanislas Lagarde, (unknown), Tijl Grootswagers, (unknown), (unknown), L.G. Vuurpijl, Pim Haselager, I.G. Sprinkhuizen-Kuyper, Martijn van Otterlo, Guido de Croon	5
8	Kinetic Online Trajectory Recovery from Static Images of Handwriting 2010 ·Paul K. Gerke	1

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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