Publications

Patrick Ebel, Julia Orlovska, Sebastian Hünemeyer, Casper Wickman, Andreas Vogelsang, and Rikard Söderberg. Automotive UX design and data-driven development: Narrowing the gap to support practitioners. Transportation Research Interdisciplinary Perspectives, (11):100455, 2021. [PUMA: UX practitioners development data-driven design support Automotive] URL

Jan Gaebel, Hans-Georg Wu, Alexander Oeser, Mario A Cypko, Matthaeus Stoehr, Andreas Dietz, Thomas Neumuth, Stefan Franke, and Steffen Oeltze-Jafra. Modeling and processing up-to-dateness of patient information in probabilistic therapy decision support. Artif. Intell. Med., (104)101842:101842, Elsevier BV, April 2020. [PUMA: Therapy decision modules; Decision neck delay; Arden and logic system; Medical model syntax; oncology; support Head]

Nora Grieb, Lukas Schmierer, Hyeon Ung Kim, Sarah Strobel, Christian Schulz, Tim Meschke, Anne Sophie Kubasch, Annamaria Brioli, Uwe Platzbecker, Thomas Neumuth, Maximilian Merz, and Alexander Oeser. A digital twin model for evidence-based clinical decision support in multiple myeloma treatment. Frontiers in Digital Health, (5)Frontiers Media SA, December 2023. [PUMA: twin clinical decision multiple myeloma evidence-based support treatment digital] URL

Katja Hoffmann, Katja Cazemier, Christoph Baldow, Silvio Schuster, Yuri Kheifetz, Sibylle Schirm, Matthias Horn, Thomas Ernst, Constanze Volgmann, Christian Thiede, Andreas Hochhaus, Martin Bornhäuser, Meinolf Suttorp, Markus Scholz, Ingmar Glauche, Markus Loeffler, and Ingo Roeder. Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology. BMC Med. Inform. Decis. Mak., (20)1:28, February 2020. [PUMA: decision-making; workflow; Haematology; Support Mathematical therapy Clinical Data Routine treatment management; simulation; modelling; system optimization; Individual Computer planning; Model-based]

Adrian Lindenmeyer, Malte Blattmann, Stefan Franke, Thomas Neumuth, and Daniel Schneider. Inadequacy of common stochastic neural networks for reliable clinical decision support. 2024. [PUMA: reliable clinical decision neural Inadequacy stochastic support networks] URL

David Nam, Julius Chapiro, Valerie Paradis, Tobias Paul Seraphin, and Jakob Nikolas Kather. Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: a disease; HCC, or intelligence; liver multivariable non-alcoholic multimodal ML, artificial WSIs, images; prediction support integration TACE, DICOM, AI, network; deep neural Digital Diagnosis; MVI, transarterial fatty topic_lifescience microvascular convolutional in learning; imaging; Communications invasion; NAFLD, chemoembolisation; hepatocellular Reporting steatohepatitis; Transparent Individual slide machine Prognosis Artificial data for NASH, whole Medicine; TRIPOD, of CNN, and Imaging carcinoma; diagnostic system; model]