NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study
Schapranow, M.-P.; Bayat, M.; Rasheed, A.; Naik, M.; Graf, V.; Schmidt, D.; Budde, K.; Cardinal, H.; Sapir-Pichhadze, R.; Fenninger, F.; Sherwood, K.; Keown, P.; Günther, O. P.; Pandl, K. D.; Leiser, F.; Thiebes, S.; Sunyaev, A.; Niemann, M.; Schimanski, A.; Klein, T.
2023. JMIR Research Protocols, 12, Art.-Nr.: e48892. doi:10.2196/48892

Trustworthy decentralized machine learning systems. Dissertation
Pandl, K. D.
2023, Oktober 16. Karlsruher Institut für Technologie (KIT)

Artificial Intelligence as a Service – Classification and Research Directions
Lins, S.; Pandl, K. D.; Teigeler, H.; Thiebes, S.; Bayer, C.; Sunyaev, A.
2021. Business & information systems engineering, 63, 441–456. doi:10.1007/s12599-021-00708-w

How detection ranges and usage stops impact digital contact tracing effectiveness for COVID-19
Pandl, K. D.; Thiebes, S.; Schmidt-Kraepelin, M.; Sunyaev, A.
2021. Scientific reports, 11 (1), Art.-Nr.: 9414. doi:10.1038/s41598-021-88768-6

Trustworthy machine learning for health care: scalable data valuation with the shapley value
Pandl, K. D.; Feiland, F.; Thiebes, S.; Sunyaev, A.
2021. CHIL ’21: Proceedings of the Conference on Health, Inference, and Learning, April, 2021. Ed.: M. Ghassemi, 47–57, Association for Computing Machinery (ACM). doi:10.1145/3450439.3451861

What Your Radiologist Might be Missing: Using Machine Learning to Identify Mislabeled Instances of X-ray Images
Rädsch, T.; Eckhardt, S.; Leiser, F.; Pandl, K. D.; Thiebes, S.; Sunyaev, A.
2021. Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS)

Drivers and Inhibitors for Organizations’ Intention to Adopt Artificial Intelligence as a Service
Pandl, K. D.; Teigeler, H.; Lins, S.; Thiebes, S.; Sunyaev, A.
2021. Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS). doi:10.24251/HICSS.2021.215

On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda
Pandl, K. D.; Thiebes, S.; Schmidt-Kraepelin, M.; Sunyaev, A.
2020. IEEE access, 8, 57075–57095. doi:10.1109/ACCESS.2020.2981447

Optimization of system parameters for an online driving style recognition
Dorr, D.; Pandl, K. D.; Gauterin, F.
2016. IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil, 1–4 November 2016, 302–307, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITSC.2016.7795571