| A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study JJ Swen, CH van der Wouden, LEN Manson, H Abdullah-Koolmees, ... The Lancet 401 (10374), 347-356, 2023 | 497 | 2023 |
| Incidence of exposure of patients in the United States to multiple drugs for which pharmacogenomic guidelines are available M Samwald, H Xu, K Blagec, PE Empey, DC Malone, SM Ahmed, P Ryan, ... PloS one 11 (10), e0164972, 2016 | 99 | 2016 |
| Gpt-3 models are poor few-shot learners in the biomedical domain M Moradi, K Blagec, F Haberl, M Samwald arXiv preprint arXiv:2109.02555, 2021 | 94 | 2021 |
| Implementing pharmacogenomics decision support across seven European countries: The Ubiquitous Pharmacogenomics (U-PGx) project K Blagec, R Koopmann, M Crommentuijn–van Rhenen, I Holsappel, ... Journal of the American Medical Informatics Association 25 (7), 893-898, 2018 | 92 | 2018 |
| Mapping global dynamics of benchmark creation and saturation in artificial intelligence S Ott, A Barbosa-Silva, K Blagec, J Brauner, M Samwald Nature Communications 13 (1), 6793, 2022 | 88 | 2022 |
| A critical analysis of metrics used for measuring progress in artificial intelligence K Blagec, G Dorffner, M Moradi, M Samwald arXiv preprint arXiv:2008.02577, 2020 | 60 | 2020 |
| A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks K Blagec, A Barbosa-Silva, S Ott, M Samwald Scientific Data 9 (1), 322, 2022 | 59 | 2022 |
| A global analysis of metrics used for measuring performance in natural language processing K Blagec, G Dorffner, M Moradi, S Ott, M Samwald Proceedings of NLP Power! The First Workshop on Efficient Benchmarking in …, 2022 | 59 | 2022 |
| Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionals K Blagec, J Kraiger, W Frühwirt, M Samwald Journal of Biomedical Informatics 137, 104274, 2023 | 58 | 2023 |
| Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study K Blagec, KM Romagnoli, RD Boyce, M Samwald PeerJ 4, e1671, 2016 | 51 | 2016 |
| Fast and scalable neural embedding models for biomedical sentence classification A Agibetov, K Blagec, H Xu, M Samwald BMC bioinformatics 19 (1), 541, 2018 | 48 | 2018 |
| Pharmacogenomics decision support in the U-PGx project: results and advice from clinical implementation across seven European countries K Blagec, JJ Swen, R Koopmann, KC Cheung, ... PloS one 17 (6), e0268534, 2022 | 47 | 2022 |
| Neural sentence embedding models for semantic similarity estimation in the biomedical domain K Blagec, H Xu, A Agibetov, M Samwald BMC bioinformatics 20 (1), 178, 2019 | 37 | 2019 |
| Digital health understanding and preparedness of medical students: a cross-sectional study M Baumgartner, C Sauer, K Blagec, G Dorffner Medical education online 27 (1), 2114851, 2022 | 35 | 2022 |
| An ontology-based, mobile-optimized system for pharmacogenomic decision support at the point-of-care JA Minarro-Gimenez, K Blagec, RD Boyce, KP Adlassnig, M Samwald PLoS One 9 (5), e93769, 2014 | 22 | 2014 |
| Ubiquitous Pharmacogenomics Consortium. A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover … JJ Swen, CH van der Wouden, LE Manson, H Abdullah-Koolmees, ... Lancet 401 (10374), 347-356, 2023 | 20 | 2023 |
| The importance of gene-drug-drug-interactions in pharmacogenomics decision support: an analysis based on Austrian claims data K Blagec, W Kuch, M Samwald Health Informatics Meets eHealth, 121-127, 2017 | 13 | 2017 |
| A critical analysis of metrics used for measuring progress in artificial intelligence. arXiv 2020 K Blagec, G Dorffner, M Moradi, M Samwald arXiv preprint arXiv:2008.02577, 2024 | 12 | 2024 |
| Deep learning models are not robust against noise in clinical text M Moradi, K Blagec, M Samwald arXiv preprint arXiv:2108.12242, 2021 | 12 | 2021 |
| Analyzing the potential for incorrect haplotype calls with different pharmacogenomic assays in different populations: a simulation based on 1000 Genomes data M Samwald, K Blagec, S Hofer, RR Freimuth Pharmacogenomics 16 (15), 1713-1721, 2015 | 12 | 2015 |
