| Application of image processing and convolutional neural networks for flood image classification and semantic segmentation RJ Pally, N Humaira, N Hubig, S Samadi Environmental modelling & software 148, 105285, 2022 | 123 | 2022 |
| The emergence of large language models as tools in literature reviews: a large language model-assisted systematic review N Hubig, D Scherbakov, V Jansari, A Bakumenko, LA Lenert Journal of the American Medical Informatics Association 32 (6), 1071-1086, 2025 | 99* | 2025 |
| SQL-and Operator-centric Data Analytics in Relational Main-Memory Databases. L Passing, M Then, NC Hubig, H Lang, M Schreier, S Günnemann, ... EDBT, 84-95, 2017 | 69 | 2017 |
| Active density-based clustering ST Mai, X He, N Hubig, C Plant, C Böhm 2013 IEEE 13th International Conference on Data Mining, 508-517, 2013 | 43 | 2013 |
| Ontologies applied in clinical decision support system rules: Systematic review X Jing, H Min, Y Gong, P Biondich, D Robinson, T Law, C Nohr, ... JMIR medical informatics 11, e43053, 2023 | 37* | 2023 |
| Generalized independent subspace clustering W Ye, S Maurus, N Hubig, C Plant 2016 IEEE 16th international conference on data mining (ICDM), 569-578, 2016 | 37 | 2016 |
| An end‐to‐end flood stage prediction system using deep neural networks L Windheuser, R Karanjit, R Pally, S Samadi, NC Hubig Earth and Space Science 10 (1), e2022EA002385, 2023 | 26 | 2023 |
| Natural language processing and social determinants of health in mental health research: AI-assisted scoping review DA Scherbakov, NC Hubig, LA Lenert, AV Alekseyenko, JS Obeid JMIR Mental Health 12 (1), e67192, 2025 | 21 | 2025 |
| Advancing Anomaly Detection: Non-Semantic Financial Data Encoding With Large Language Models A Bakumenko, K Hlaváčková-Schindler, C Plant, NC Hubig IEEE Access, 2025 | 17* | 2025 |
| Hyperinsight: Data exploration deep inside hyper N Hubig, L Passing, ME Schüle, D Vorona, A Kemper, T Neumann Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 17 | 2017 |
| Compression-based graph mining exploiting structure primitives J Feng, X He, N Hubig, C Böhm, C Plant 2013 IEEE 13th International Conference on Data Mining, 181-190, 2013 | 17 | 2013 |
| Opening the black box of family-based treatments: an artificial intelligence framework to examine therapeutic alliance and therapist empathy PB Cunningham, J Gilmore, S Naar, SD Preston, CF Eubanks, NC Hubig, ... Clinical child and family psychology review 26 (4), 975-993, 2023 | 15 | 2023 |
| FlowDyn: A daily streamflow prediction pipeline for dynamical deep neural network applications SS Tabas, N Humaira, S Samadi, NC Hubig Environmental Modelling & Software 170, 105854, 2023 | 12 | 2023 |
| Detection and prediction of natural hazards using large-scale environmental data N Hubig, P Fengler, A Züfle, R Yang, S Günnemann International Symposium on Spatial and Temporal Databases, 300-316, 2017 | 12 | 2017 |
| DX-FloodLine: End-To-End deep explainable pipeline for real time flood scene object detection from multimedia images N Humaira, VS Samadi, NC Hubig IEEE Access 11, 110644-110655, 2023 | 11 | 2023 |
| Effiziente Integration von Data-und Graph-Mining-Algorithmen in relationale Datenbanksysteme. M Then, L Passing, NC Hubig, S Günnemann, A Kemper, T Neumann LWA, 45-49, 2015 | 8 | 2015 |
| Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features A Haque, D Stubbs, NC Hubig, FG Spinale, WJ Richardson BMC Medical Informatics and Decision Making 22 (1), 282, 2022 | 7 | 2022 |
| Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamics J Mei, A Rodriguez-Garcia, D Takeuchi, G Wainstein, N Hubig, ... arXiv preprint arXiv:2501.06762, 2025 | 6 | 2025 |
| A systematic approach to configuring MetaMap for optimal performance X Jing, A Indani, N Hubig, H Min, Y Gong, JJ Cimino, DF Sittig, L Rennert, ... Methods of Information in Medicine 61 (S 02), e51-e63, 2022 | 5 | 2022 |
| New Frontiers of Human-centered Explainable AI (HCXAI): Participatory Civic AI, Benchmarking LLMs, XAI Hallucinations, and Responsible AI Audits U Ehsan, EA Watkins, P Wintersberger, C Manger, N Hubig, S Savage, ... Proceedings of the Extended Abstracts of the CHI Conference on Human Factors …, 2025 | 4 | 2025 |
Claudia PlantProfessor of Computer Science, leader of research group Data Mining and Machine Learning, UniVieVerified email at univie.ac.at
