Publications

Wolfgang Kircheis, Marion Schmidt, Arno Simons, Benno Stein, und Martin Potthast. Mining the History Sections of Wikipedia Articles on Science and Technology. 2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 200-204, 2023. [PUMA: Disputes Encyclopedias Filtering Focusing Innovation Internet Libraries Priority Science Studies Technological Technology Transforms Wikipedia and innovation zno]

Oliver Kirsten, Martin Bogdan, und Sophie Adama. Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: Complexity Computational Consciousness Information Locked-In Measures Modeling Neuroscience Prediction Predictive Processing Signal Syndrome Theory Training algorithms and data learning modeling models processing zno machine]

Andre de Carvalho, Robson Bonidia, Jude Dzevela Kong, Mariana Dauhajre, Claudio Struchiner, Guilherme Goedert, Peter F. Stadler, Maria Emilia Walter, Danilo Sanches, Troy Day, Marcia Castro, John Edmunds, Manuel Colome-Hidalgo, Demian Arturo Herrera Morban, Edian F. Franco, Cesar Ugarte-Gil, Patricia Espinoza-Lopez, Gabriel Carrasco-Escobar, und Ulisses Rocha. Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries. arXiv, 2024. [PUMA: Computer FOS Intelligence and information sciences zno artificial] URL

Tom Richard Vargis, und Siavash Ghiasvand. A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, Januar 2022. [PUMA: Cluster Computer Computing, Distributed, Learning Machine Parallel, Science and myOwn] URL

Tom Richard Vargis, und Siavash Ghiasvand. Content-Aware Depth-Adaptive Image Restoration. Proceedings of the 29th International Conference on Automation and Computing, Sunderland, UK, Januar 2024. [PUMA: Computer Learning, Machine Pattern Recognition, Science Vision and myOwn] URL

Oscar J. Pellicer-Valero, Miguel-Ángel Fernández-Torres, Chaonan Ji, Miguel D. Mahecha, und Gustau Camps-Valls. Explainable Earth Surface Forecasting under Extreme Events. arXiv, 2024. [PUMA: (cs.LG), Computer FOS: Learning Machine and information sciences sciences, topic_earthenvironment] URL

Aryaman Gupta, Ulrik Günther, Pietro Incardona, Guido Reina, Steffen Frey, Stefan Gumhold, und Ivo F. Sbalzarini. Efficient Raycasting of View-Dependent Piecewise Constant Representations of Volumetric Data. 17.06.2022. [PUMA: FIS_scads Human-centered Visualization Visualization, and computing, concepts paradigms, techniques theory, topic_lifescience topic_visualcomputing xack]

Kim Breitwieser, Allison Lahnala, Charles Welch, Lucie Flek, und Martin Potthast. Modeling Proficiency with Implicit User Representations. arXiv, 2021. [PUMA: (cs.CL), Computation Computer FOS: Language and information sciences sciences, zno] URL

Jan Gaebel, Hans-Georg Wu, Alexander Oeser, Mario A Cypko, Matthaeus Stoehr, Andreas Dietz, Thomas Neumuth, Stefan Franke, und 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: Arden Decision Head Medical Therapy and decision delay logic model modules neck oncology support syntax system zno]

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

Scarlet Brockmoeller, Amelie Echle, Narmin Ghaffari Laleh, Susanne Eiholm, Marie Louise Malmstrøm, Tine Plato Kuhlmann, Katarina Levic, Heike Irmgard Grabsch, Nicholas P West, Oliver Lester Saldanha, Katerina Kouvidi, Aurora Bono, Lara R Heij, Titus J Brinker, Ismayil Gögenür, Philip Quirke, und Jakob Nikolas Kather. Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J. Pathol., (256)3:269--281, Wiley, März 2022. [PUMA: AI; LNM adipose and artificial bowel colorectal deep digital early inflamed metastasis; new pT1 pT2 prediction predictive tissue; topic_lifescience zno learning intelligence pathology biomarker cancer]