15.	03/23		J. Li, A. Dada, J. Kleesiek, J. Egger
			“ChatGPT in Healthcare: A Taxonomy and Systematic Review”
			medRxiv preprint, pp. 1-30, 2023. (Link) (pdf)
14.	03/23		M. Eisenmann, et al.
			“Why is the winner the best?”
			arXiv preprint, pp. 1-23, 2023. (Link) (pdf)
13.	03/23		F. Hörst, S. Ting, S.-T. Liffers, K. L Pomykala, K. Steiger, M. Albertsmeier, M. K. Angele, S. Lorenzen, M. Quante, W. Weichert, J. Egger, J. T. Siveke, J. Kleesiek
			“Histology-based Prediction of Therapy Response to Neoadjuvant Chemotherapy for Esophageal and Esophagogastric Junction Adenocarcinomas Using Deep Learning”
			medRxiv preprint, pp. 1-11, 2023. (Link)
12.	12/22		M. Eisenmann, et al.
			“Biomedical image analysis competitions: The state of current participation practice”
			arXiv preprint, pp. 1-29, 2022. (Link)
11.	11/22		J. Li, A. Ferreira, B. Puladi, V. Alves, M. Kamp, M.-S. Kim, F. Nensa, J. Kleesiek, S.-A. Ahmadi, J. Egger
			“Open-Source Skull Reconstruction with MONAI”
			arXiv preprint, pp. 1-7, 2022. (Link)
10.	10/22		C. Strack, K. L. Pomykala, H.-P. Schlemmer, J. Egger, J. Kleesiek
			“A net for everyone: fully personalized and unsupervised neural networks trained with longitudinal data from a single patient”
			arXiv preprint, pp. 1-15, 2022. (Link)
9.	10/22		L. Heiliger, Z. Marinov, M. Hasin, A. Ferreira, J. Fragemann, K. Pomykala, J. Murray, D. Kersting, V. Alves, R. Stiefelhagen, J. Egger, J. Kleesiek
			“AutoPET Challenge: Combining nn-Unet with Swin UNETR Augmented by Maximum Intensity Projection Classifier”
			arXiv preprint, pp. 1-12, 2022. (Link)
8.	07/22		A. Ferreira, J. Li, K. L. Pomykala, J. Kleesiek, V. Alves, J. Egger
			“GAN-based generation of realistic 3D data: A systematic review and taxonomy”
			arXiv preprint, pp. 1-52, 2022. (Link)
7.	05/22		M. Rempe, F. Mentzel, K. L. Pomykala, J. Haubold, F. Nensa, K. Kröninger, J. Egger, J. Kleesiek
			“k-strip: A novel segmentation algorithm in k-space for the application of skull stripping”
			arXiv preprint, pp. 1-11, 2022. (Link)
6.	04/22		J. Li, D. G. Ellis, A. Pepe, C. Gsaxner, M. R. Aizenberg, J. Kleesiek, J. Egger
			“Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model”
			arXiv preprint, pp. 1-9, 2022. (Link)
5.	03/22		J. Fragemann, L. Ardizzone, J. Egger, J. Kleesiek
			“Review of Disentanglement Approaches for Medical Applications - Towards Solving the Gordian Knot of Generative Models in Healthcare”
			arXiv preprint, pp. 1-43, 2022. (Link)
4.	02/22		J. Li, C. Gsaxner, A. Pepe, D. Schmalstieg, J. Kleesiek, J. Egger
			“Sparse Convolutional Neural Networks for Medical Image Analysis”
			TechRxiv preprint, pp. 1-12, 2022. (Link)
3.	02/22		L. Heiliger, A. Sekuboyina, B. Menze, J. Egger, J. Kleesiek
			“Beyond Medical Imaging - A Review of Multimodal Deep Learning in Radiology”
			TechRxiv preprint, pp. 1-12, 2022. (Link)
2.	11/21		A. Pepe, J. Egger, M. Codari, M. J. Willemink, C. Gsaxner, J. Li, P. M. Roth, G. Mistelbauer, D. Schmalstieg, D. Fleischmann
			“Automated cross-sectional view selection in CT angiography of aortic dissections with uncertainty awareness and retrospective clinical annotations”
			arXiv preprint, pp. 1-28, 2021. (Link)
1.	08/21		Y. Jin, A. Pepe, J. Li, C. Gsaxner, F.-h. Zhao, K. L. Pomykala, J. Kleesiek, A. F. Frangi, J. Egger
			“AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo”
			arXiv preprint, pp. 1-49, 2021. (Link)