Publications of Steven Schalekamp

2022

Papers in international journals

1. 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
2. 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
3. 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
4. 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

Abstracts

1. 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
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