Transfer Learning for Domain-Specific Named Entity Recognition in German. - Sunna Torge 001; Waldemar Hahn; René Jäkel (CIST, 2021)

Corpus and Baseline Model for Domain-Specific Entity Recognition in German. - Sunna Torge 001; Waldemar Hahn; René Jäkel; Wolfgang E. Nagel (CIST, 2021)

Word2Vec Embeddings for Categorical Values in Synthetic Tabular Generation. - Waldemar Hahn; Martin Sedlmayr; Markus Wolfien (CSCI, 2022)

Convex space learning improves deep-generative oversampling for tabular imbalanced classification on smaller datasets. - Kristian Schultz; Saptarshi Bej; Waldemar Hahn; Markus Wolfien; Prashant Srivastava; Olaf Wolkenhauer (CoRR, 2022)

Context-Sensitive Common Data Models for Genetic Rare Diseases - A Concept. - Najia Ahmadi; Michele Zoch; Brita Sedlmayr; Katharina Schuler; Waldemar Hahn; Martin Sedlmayr; Markus Wolfien (ICIMTH, 2023)

Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence. - Jan-Niklas Eckardt; Waldemar Hahn; Christoph Röllig; Sebastian Stasik; Uwe Platzbecker; Carsten Müller-Tidow; Hubert Serve; Claudia D. Baldus; Christoph Schliemann; Kerstin Schäfer-Eckart; Maher Hanoun; Martin Kaufmann; et al. (npj Digit. Medicine, 2024)

ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. - Kristian Schultz; Saptarshi Bej; Waldemar Hahn; Markus Wolfien; Prashant Srivastava; Olaf Wolkenhauer (Pattern Recognit., 2024)

Generating Reliable Synthetic Clinical Trial Data: The Role of Hyperparameter Optimization and Domain Constraints. - Waldemar Hahn; Jan-Niklas Eckardt; Christoph Röllig; Martin Sedlmayr; Jan Moritz Middeke; Markus Wolfien (CoRR, 2025)

Context factors in clinical decision-making: a scoping review. - Katharina Schuler; Ian-Christopher Jung; Maria Zerlik; Waldemar Hahn; Martin Sedlmayr; Brita Sedlmayr (BMC Medical Informatics Decis. Mak., 2025)