Sarah J. van Riel

2.0k citations

10 papers · 1.4k indexed · 1 hit paper · h-index 8

Radiology, Nuclear Medicine and Imaging top 1%
Pulmonary and Respiratory Medicine top 5%
Artificial Intelligence top 5%
Computer Vision and Pattern Recognition top 5%
Biomedical Engineering

Co-authors: Bram van Ginneken Francesco Ciompi Colin Jacobs Clara I. Sá‎nchez Matiullah Naqibullah Mathilde Marie Winkler Wille Arnaud A. A. Setio Geert Litjens
Topics: Radiomics and Machine Learning in Medical Imaging (10 papers)Lung Cancer Diagnosis and Treatment (10 papers)Lung Cancer Treatments and Mutations (4 papers)
Cited by: Radiology, Nuclear Medicine and Imaging Health Informatics Pulmonary and Respiratory Medicine
Journals: PLoS ONE Radiology IEEE Transactions on Medical Imaging
Partner nations: Netherlands Denmark Germany

In The Last Decade

Sarah J. van Riel

10 papers receiving 1.4k 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.

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 Sarah J. van Riel

Since Specialization

Citations

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

Fields of papers citing papers by Sarah J. van Riel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sarah J. van Riel. 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 Sarah J. van Riel. The network helps show where Sarah J. van Riel may publish in the future.

Co-authorship network of co-authors of Sarah J. van Riel

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah J. van Riel. A scholar is included among the top collaborators of Sarah J. van Riel 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 Sarah J. van Riel. Sarah J. van Riel 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:

10 of 10 papers shown

#	Work	Indexed citations
1	Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement 2021 ·Radiology Imaging Cancer ·Colin Jacobs,Anton Schreuder,Sarah J. van Riel,Ernst T. Scholten,Rianne Wittenberg,Mathilde Marie Winkler Wille,Bartjan de Hoop,Ralf W. Sprengers,Onno M. Mets,Bram Geurts,Mathias Prokop,Cornelia Schaefer‐Prokop,Bram van Ginneken	21
2	Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management 2018 ·European Radiology ·Sarah J. van Riel,Colin Jacobs,Ernst T. Scholten,Rianne Wittenberg,Mathilde Marie Winkler Wille,Bartjan de Hoop,Ralf W. Sprengers,Onno M. Mets,Bram Geurts,Mathias Prokop,Cornelia Schaefer‐Prokop,Bram van Ginneken	44
3	Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines 2017 ·European Radiology ·Sarah J. van Riel,Francesco Ciompi,Colin Jacobs,Mathilde Marie Winkler Wille,Ernst T. Scholten,Matiullah Naqibullah,Stephen Lam,Mathias Prokop,Cornelia Schaefer‐Prokop,Bram van Ginneken	39
4	Malignancy risk estimation of pulmonary nodules in screening CTs: Comparison between a computer model and human observers 2017 ·PLoS ONE ·Sarah J. van Riel,Francesco Ciompi,Mathilde Marie Winkler Wille,Asger Dirksen,Stephen Lam,Ernst T. Scholten,Santiago E. Rossi,Nicola Sverzellati,Matiullah Naqibullah,Rianne Wittenberg,(unknown),Miranda Snoeren,Liesbeth Peters-Bax,Onno M. Mets,Monique Brink,Mathias Prokop,Cornelia Schaefer‐Prokop,Bram van Ginneken	28
5	Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networksbreakdown → 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
6	Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box 2015 ·Medical Image Analysis ·Francesco Ciompi,Bartjan de Hoop,Sarah J. van Riel,Kaman Chung,Ernst T. Scholten,Matthijs Oudkerk,Pim A. de Jong,Mathias Prokop,Bram van Ginneken	211
7	Observer Variability for Classification of Pulmonary Nodules on Low-Dose CT Images and Its Effect on Nodule Management 2015 ·Radiology ·Sarah J. van Riel,Clara I. Sá‎nchez,Alexander A. Bankier,David P. Naidich,Johny Verschakelen,Ernst T. Scholten,Pim A. de Jong,Colin Jacobs,Eva M. van Rikxoort,Liesbeth Peters-Bax,Miranda Snoeren,Mathias Prokop,Bram van Ginneken,Cornelia Schaefer‐Prokop	137
8	Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial 2015 ·European Radiology ·Mathilde Marie Winkler Wille,Sarah J. van Riel,Zaigham Saghir,Asger Dirksen,Jesper Holst Pedersen,Colin Jacobs,Laura H. Thomsen,Ernst T. Scholten,Lene Theil Skovgaard,Bram van Ginneken	62
9	Computer-aided detection of lung cancer: combining pulmonary nodule detection systems with a tumor risk prediction model 2015 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·Arnaud A. A. Setio,Colin Jacobs,Francesco Ciompi,Sarah J. van Riel,Mathilde Marie Winkler Wille,Asger Dirksen,Eva M. van Rikxoort,Bram van Ginneken	3
10	Automatic detection of spiculation of pulmonary nodules in computed tomography images 2015 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·Francesco Ciompi,Colin Jacobs,Ernst T. Scholten,Sarah J. van Riel,Mathilde Marie Winkler Wille,Mathias Prokop,Bram van Ginneken	3

About Sarah J. van Riel

Sarah J. van Riel is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 10 papers that have together received 1.4k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Lung Cancer Diagnosis and Treatment (10 papers) and Lung Cancer Treatments and Mutations (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.1k citations), Health Informatics (39 citations) and Pulmonary and Respiratory Medicine (834 citations). Sarah J. van Riel has collaborated with scholars based in Netherlands, Denmark and Germany. Frequent co-authors include Bram van Ginneken, Francesco Ciompi, Colin Jacobs, Clara I. Sá‎nchez, Matiullah Naqibullah, Mathilde Marie Winkler Wille, Arnaud A. A. Setio, Geert Litjens, Paul K. Gerke and Ernst T. Scholten. Their work appears in journals such as PLoS ONE, Radiology and IEEE Transactions on Medical Imaging.

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