Publications of Steven Schalekamp

Papers in international journals

  1. K. van Leeuwen, S. Schalekamp, M. Rutten, M. Huisman, C. Schaefer-Prokop, M. de Rooij, B. van Ginneken, B. Maresch, B. Geurts, C. van Dijke, E. Laupman-Koedam, E. Hulleman, E. Verhoeff, E. Meys, F. Mohamed Hoesein, F. ter Brugge, F. van Hoorn, F. van der Wel, I. van den Berk, J. Luyendijk, J. Meakin, J. Habets, J. Verbeke, J. Nederend, K. Meys, L. Deden, L. Langezaal, M. Nasrollah, M. Meij, M. Boomsma, M. Vermeulen, M. Vestering, O. Vijlbrief, P. Algra, S. Algra, S. Bollen, T. Samson, Y. von Brucken Fock, B. Maresch, B. Geurts, C. van Dijke, E. Laupman-Koedam, E. Hulleman, E. Verhoeff, E. Meys, F. Mohamed Hoesein, F. ter Brugge, F. van Hoorn, F. van der Wel, I. van den Berk, J. Luyendijk, J. Meakin, J. Habets, J. Verbeke, J. Nederend, K. Meys, L. Deden, L. Langezaal, M. Nasrollah, M. Meij, M. Boomsma, M. Vermeulen, M. Vestering, O. Vijlbrief, P. Algra, S. Algra, S. Bollen, T. Samson, Y. von Brucken Fock and F. the Group, "Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction", Radiology, 2024;310.
    Abstract DOI PMID Cited by ~3
  2. K. Murphy, J. Muhairwe, S. Schalekamp, B. van Ginneken, I. Ayakaka, K. Mashaete, B. Katende, A. van Heerden, S. Bosman, T. Madonsela, L. Gonzalez Fernandez, A. Signorell, M. Bresser, K. Reither and T. Glass, "COVID-19 screening in low resource settings using artificial intelligence for chest radiographs and point-of-care blood tests", Scientific Reports, 2023;13.
    Abstract DOI PMID
  3. W. Hendrix, N. Hendrix, E. Scholten, M. Mourits, J. Trap-de Jong, S. Schalekamp, M. Korst, M. van Leuken, B. van Ginneken, M. Prokop, M. Rutten and C. Jacobs, "Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans", Communications Medicine, 2023;3(1):156.
    Abstract DOI PMID Algorithm
  4. K. Leeuwen, M. Becks, D. Grob, F. de Lange, J. Rutten, S. Schalekamp, M. Rutten, B. van Ginneken, M. de Rooij and F. Meijer, "AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation", Heliyon, 2023;9(8).
    Abstract DOI
  5. K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "Clinical use of artificial intelligence products for radiology in the Netherlands between 2020 and 2022", European Radiology, 2023.
    Abstract DOI Cited by ~5
  6. E. De Kort, J. Buil, S. Schalekamp, C. Schaefer-Prokop, P. Verweij, N. Schaap, N. Blijlevens and W. der Van Velden, "Invasive Fungal Disease in Patients with Myeloid Malignancies: A Retrospective Cohort Study of a Diagnostic-Driven Care Pathway Withholding Mould-Active Prophylaxis", Journal of Fungi, 2022;8:925.
    Abstract DOI PMID Cited by ~2
  7. E. Calli, K. Murphy, E. Scholten, S. Schalekamp and B. van Ginneken, "Explainable emphysema detection on chest radiographs with deep learning", PLoS One, 2022;17(7):e0267539.
    Abstract DOI PMID Cited by ~2
  8. K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "How does artificial intelligence in radiology improve efficiency and health outcomes?", Pediatric Radiology, 2022;52(11):2087-2093.
    Abstract DOI PMID Cited by ~70
  9. S. Schalekamp, W. Klein and K. van Leeuwen, "Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective", Pediatric Radiology, 2022;52(11):2120-2130.
    Abstract DOI
  10. C. Jacobs, A. Setio, E. Scholten, P. Gerke, H. Bhattacharya, F. M. Hoesein, M. Brink, E. Ranschaert, P. de Jong, M. Silva, B. Geurts, K. Chung, S. Schalekamp, J. Meersschaert, A. Devaraj, P. Pinsky, S. Lam, B. van Ginneken and K. Farahani, "Deep Learning for Lung Cancer Detection in Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists", Radiology: Artificial Intelligence, 2021;3(6):e210027.
    Abstract DOI PMID Download Cited by ~26
  11. K. van Leeuwen, S. Schalekamp, M. Rutten, B. van Ginneken and M. de Rooij, "Artificial intelligence in radiology: 100 commercially available products and their scientific evidence", European Radiology, 2021;31:3797-3804.
    Abstract DOI PMID Cited by ~172
  12. N. Lessmann, C. Sánchez, L. Beenen, L. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. van Everdingen, P. Gerke, B. Geurts, H. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H. Huisman, I. Isgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop and B. van Ginneken, "Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence", Radiology, 2021;298(1):E18-E28.
    Abstract DOI PMID Algorithm Download Cited by ~112
  13. K. van Leeuwen, F. Meijer, S. Schalekamp, M. Rutten, E. van Dijk, B. van Ginneken, T. Govers and M. Rooij, "Cost - effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment", Insights into Imaging, 2021;12:133.
    Abstract DOI Cited by ~18
  14. N. Hendrix, E. Scholten, B. Vernhout, S. Bruijnen, B. Maresch, M. de Jong, S. Diepstraten, S. Bollen, S. Schalekamp, M. de Rooij, A. Scholtens, W. Hendrix, T. Samson, L. Sharon Ong, E. Postma, B. van Ginneken and M. Rutten, "Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs", Radiology: Artificial Intelligence, 2021:e200260.
    Abstract DOI Algorithm Download Cited by ~19
  15. S. Schalekamp, M. Huisman, R. van Dijk, M. Boomsma, P. Freire Jorge, W. de Boer, G. Herder, M. Bonarius, O. Groot, E. Jong, A. Schreuder and C. Schaefer-Prokop, "Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19", Radiology, 2020:202723.
    Abstract DOI PMID Cited by ~72
  16. K. Murphy, H. Smits, A. Knoops, M. Korst, T. Samson, E. Scholten, S. Schalekamp, C. Schaefer-Prokop, R. Philipsen, A. Meijers, J. Melendez, B. van Ginneken and M. Rutten, "COVID-19 on the Chest Radiograph: A Multi-Reader Evaluation of an AI System", Radiology, 2020;296:E166-E172.
    Abstract DOI PMID Cited by ~154
  17. K. Murphy, S. Habib, S. Zaidi, S. Khowaja, A. Khan, J. Melendez, E. Scholten, F. Amad, S. Schalekamp, M. Verhagen, R. Philipsen, A. Meijers and B. van Ginneken, "Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system", Scientific Reports, 2020;10:5492.
    Abstract DOI PMID arXiv Cited by ~113
  18. E. Sogancioglu, K. Murphy, E. Calli, E. Scholten, S. Schalekamp and B. Van Ginneken, "Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification", IEEE Access, 2020;8:94631-94642.
    Abstract DOI Cited by ~27
  19. S. Schalekamp, N. Karssemeijer, A. Cats, B. De Hoop, B. Geurts, O. Berger-Hartog, B. van Ginneken and C. Schaefer-Prokop, "The Effect of Supplementary Bone-Suppressed Chest Radiographs on the Assessment of a Variety of Common Pulmonary Abnormalities: Results of an Observer Study", Journal of Thoracic Imaging, 2016;31(2):119-125.
    Abstract DOI PMID Download Cited by ~7
  20. S. Schalekamp, B. van Ginneken, I. van den Berk, I. Hartmann, M. Snoeren, A. Odink, W. van Lankeren, S. Pegge, L. Schijf, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression increases the visibility of invasive pulmonary aspergillosis in chest radiographs", PLoS One, 2014;9(10):e108551.
    Abstract DOI PMID Cited by ~16
  21. S. Schalekamp, B. van Ginneken, E. Koedam, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone suppressed images", Radiology, 2014;272(1):252-261.
    Abstract DOI PMID Download Cited by ~73
  22. S. Schalekamp, B. van Ginneken, E. Koedam, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer-aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone-suppressed images", Radiology, 2014;272(1):252-261.
    Abstract DOI PMID Cited by ~73
  23. S. Schalekamp, B. van Ginneken, B. Heggelman, M. Imhof-Tas, I. Somers, M. Brink, M. Spee, C. Schaefer-Prokop and N. Karssemeijer, "New methods for using computer-aided detection information for the detection of lung nodules on chest radiographs", British Journal of Radiology, 2014;87(1036):20140015.
    Abstract DOI PMID Download Cited by ~9
  24. S. Schalekamp, B. van Ginneken, N. Karssemeijer and C. Schaefer-Prokop, "Chest radiography: new technological developments and their applications", Seminars in Respiratory and Critical Care Medicine, 2014;35(1):3-16.
    Abstract DOI PMID Download Cited by ~18
  25. S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, "Influence of study design in receiver operating characteristics studies: sequential versus independent reading", Journal of Medical Imaging, 2014;1(1):015501-015501.
    Abstract DOI Cited by ~6
  26. S. Schalekamp, B. van Ginneken, L. Meiss, L. Peters-Bax, L. Quekel, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs", European Journal of Radiology, 2013;82(12):2399-2405.
    Abstract DOI PMID Download Cited by ~28

Preprints

  1. E. Sogancioglu, B. van Ginneken, F. Behrendt, M. Bengs, A. Schlaefer, M. Radu, D. Xu, K. Sheng, F. Scalzo, E. Marcus, S. Papa, J. Teuwen, E. Scholten, S. Schalekamp, N. Hendrix, C. Jacobs, W. Hendrix, C. Sánchez and K. Murphy, "Nodule detection and generation on chest X-rays: NODE21 Challenge", arXiv:2401.02192, 2024.
    Abstract DOI PMID arXiv
  2. K. Murphy, S. Habib, S. Zaidi, S. Khowaja, A. Khan, J. Melendez, E. Scholten, F. Amad, S. Schalekamp, M. Verhagen, R. Philipsen, A. Meijers and B. van Ginneken, "Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system", arXiv:1903.03349, 2019.
    Abstract arXiv Cited by ~113

Papers in conference proceedings

  1. S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, "Impact of Bone Suppression Imaging on the Detection of Lung Nodules in Chest Radiographs: Analysis of Multiple Reading Sessions", Medical Imaging, 2013:86730Y.
    Abstract DOI Cited by ~3
  2. P. Maduskar, L. Hogeweg, R. Philipsen, S. Schalekamp and B. van Ginneken, "Improved texture analysis for automatic detection of Tuberculosis (TB) on Chest Radiographs with Bone Suppression images", Medical Imaging, 2013;8670(16):86700H.
    Abstract DOI Cited by ~28

Abstracts

  1. K. van Leeuwen, D. Hedderich and S. Schalekamp, "Potential risk of off-label use of commercially available AI-based software for radiology", European Congress of Radiology, 2023.
    Abstract
  2. K. van Leeuwen, M. Becks, S. Schalekamp, B. van Ginneken, M. Rutten, M. de Rooij and F. Meijer, "Real-world evaluation of artificial intelligence software for cerebral large vessel occlusion detection in CT angiography", European Congress of Radiology, 2022.
    Abstract
  3. M. Grauw, B. Ginneken, B. Geisler, E. Smit, M. Rooij, S. Schalekamp and M. Prokop, "Deep learning universal lesion segmentation for automated RECIST measurements on CT: comparison to manual assessment by radiologists", European Congress of Radiology, 2022.
    Abstract
  4. K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "The rise of artificial intelligence solutions in radiology departments in the Netherlands", European Congress of Radiology, 2022.
    Abstract
  5. K. van Leeuwen, F. Meijer, S. Schalekamp, M. Rutten, E. van Dijk, B. van Ginneken, T. Govers and M. de Rooij, "Artificial Intelligence in Acute Stroke: an Early Health Technology Assessment of Vessel Occlusion Detection on Computed Tomography", European Congress of Radiology, 2021.
    Abstract
  6. K. van Leeuwen, M. de Rooij, M. Rutten, B. van Ginneken and S. Schalekamp, "Performance Of A Commercial Software Package For Lung Nodule Detection On Chest Radiographs Compared With 8 Expert Readers", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  7. K. van Leeuwen, M. Rutten, S. Schalekamp, M. de Rooij and B. van Ginneken, "Clinical use of artificial intelligence in radiology departments in the Netherlands: a survey", European Congress of Radiology, 2021.
    Abstract
  8. K. van Leeuwen, M. de Rooij, M. Rutten, S. Schalekamp and B. van Ginneken, "Commercial Artificial Intelligence Solutions For Radiology: A Market Update", Annual Meeting of the Radiological Society of North America, 2021.
    Abstract
  9. K. van Leeuwen, S. Schalekamp, M. Rutten, B. van Ginneken and M. de Rooij, "Scientific Evidence for 100 Commercially Available Artificial Intelligence Tools for Radiology: A Systematic Review", Annual Meeting of the Radiological Society of North America, 2020.
    Abstract
  10. D. Grob, S. Schalekamp, L. Oostveen, W. van der Woude, C. Jacobs, M. Prokop, I. Sechopoulos and M. Brink, "Pulmonary nodule growth: can follow-up be shortened with a high-end or an ultra-high-resolution CT scanner?", European Congress of Radiology, 2020.
    Abstract
  11. R. Becks, M. Meijs, R. Manniesing, J. Vister, S. Schalekamp, R. Mann, S. Steens, E. Smit, E. van Dijk, M. Prokop and F. Meijer, "Additional Value of Brain CT Perfusion in The Detection of Intracranial Vessel Occlusion in Acute Ischemic Stroke: A (Multi Experience Level) Inter-Observer Study", Annual Meeting of the Radiological Society of North America, 2016.
    Abstract
  12. S. Schalekamp, N. Karssemeijer, C. Schaefer-Prokop and B. van Ginneken, "Double reading improves detection of small lung tumors in chest radiographs: can a computer aided detection system replace the second reader?", European Congress of Radiology, 2014.
    Abstract
  13. S. Schalekamp, I. van den Berk, I. Hartmann, M. Snoeren, A. Odink, S. Pegge, L. Schijf, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppressed images improve pulmonary fungal infection detection in chest radiographs", European Congress of Radiology, 2014.
    Abstract
  14. S. Schalekamp, B. van Ginneken, M. Brink, B. Heggelman, M. Spee, I. Somers, N. Karssemeijer and C. Schaefer-Prokop, ""Computer Aided Detection shows added value to Bone Suppression Imaging for the detection of lung nodules in chest radiographs"", WCTI, 2013.
    Abstract
  15. S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, ""Computer aided detection of lung nodules in chest radiographs: novel approaches to improve reader performance"", MIPS, 2013.
    Abstract
  16. S. van Riel, C. Schaefer-Prokop, E. van Rikxoort, B. van Ginneken, M. Prokop, S. Schalekamp, C. Jacobs, P. de Jong, H. Gietema and E. Scholten, "Impact of section thickness on classification of pulmonary nodules into solid, part-solid, and non-solid: an observer study", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  17. S. Schalekamp, N. Karssemeijer, C. Schaefer-Prokop and B. van Ginneken, ""Independent combination of multiple readers for the detection of lung nodules in chest radiographs: setting a benchmark for computer-aided detection"", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  18. S. van Riel, E. van Rikxoort, C. Jacobs, S. Schalekamp, M. Prokop, B. van Ginneken, P. de Jong, E. Scholten, H. Gietema and C. Schaefer-Prokop, "Intra- and inter-reader variability of pulmonary nodule classification according to the Fleischner guidelines: clinical consequences", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  19. S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, M. Snoeren, L. Quekel, E. Koedam, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression imaging improves observer performance for the detection of lung nodules in chest radiographs", Annual Meeting of the European Society of Thoracic Imaging, 2012.
    Abstract
  20. S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, L. Meiss, A. Tiehuis, E. Koedam, L. Quekel, M. Snoeren, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Botsuppressie in thoraxfoto's verbetert de detectie van pulmonale nodules door radiologen", Radiologen Dagen, 2012.
    Abstract
  21. S. Schalekamp, B. van Ginneken, E. Koedam, L. Quekel, M. Snoeren, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer aided detection helps radiologists to detect pulmonary nodules in chest radiographs, when having bone suppressed images available", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  22. S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, L. Meiss, A. Tiehuis, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression imaging improves observer performance for the detection of lung nodules in chest radiographs", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  23. S. Schalekamp, B. Heggelman and C. Schaefer-Prokop, ""Focal lesions on Gadoxetate disodium enhanced and diffusionweighted liver MRI: a guidance for differential diagnosis"", European Congress of Radiology, 2011.
    Abstract

PhD theses

  1. K. van Leeuwen, "Validation and implementation of commercial artificial intelligence software for radiology", PhD thesis, 2023.
    Abstract Url
  2. S. Schalekamp, "Advanced processing in chest radiography: impact on observer performance", PhD thesis, 2015.
    Abstract Url