| Interactive machine learning: experimental evidence for the human in the algorithmic loop: A case study on Ant Colony Optimization A Holzinger, M Plass, M Kickmeier-Rust, K Holzinger, GC Crişan, ... Applied Intelligence 49, 2401-2414, 2019 | 212 | 2019 |
| Digital pathology: advantages, limitations and emerging perspectives SW Jahn, M Plass, F Moinfar Journal of clinical medicine 9 (11), 3697, 2020 | 203 | 2020 |
| A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop A Holzinger, M Plass, K Holzinger, GC Crisan, CM Pintea, V Palade arXiv preprint arXiv:1708.01104, 2017 | 136 | 2017 |
| Towards interactive Machine Learning (iML): applying ant colony algorithms to solve the traveling salesman problem with the human-in-the-loop approach A Holzinger, M Plass, K Holzinger, GC Crişan, CM Pintea, V Palade Availability, Reliability, and Security in Information Systems: IFIP WG 8.4 …, 2016 | 129 | 2016 |
| Interpretable survival prediction for colorectal cancer using deep learning E Wulczyn, DF Steiner, M Moran, M Plass, R Reihs, F Tan, ... NPJ digital medicine 4 (1), 71, 2021 | 113 | 2021 |
| The explainability paradox: Challenges for xAI in digital pathology T Evans, CO Retzlaff, C Geißler, M Kargl, M Plass, H Müller, TR Kiehl, ... Future Generation Computer Systems 133, 281-296, 2022 | 69 | 2022 |
| Explainability and causability for artificial intelligence-supported medical image analysis in the context of the European In Vitro Diagnostic Regulation H Müller, A Holzinger, M Plass, L Brcic, C Stumptner, K Zatloukal New Biotechnology 70, 67-72, 2022 | 43 | 2022 |
| Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading E Wulczyn, K Nagpal, M Symonds, M Moran, M Plass, R Reihs, F Nader, ... Communications medicine 1 (1), 10, 2021 | 37 | 2021 |
| Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology A Homeyer, C Geißler, LO Schwen, F Zakrzewski, T Evans, ... Modern Pathology 35 (12), 1759-1769, 2022 | 34 | 2022 |
| Personas for artificial intelligence (AI) an open source toolbox A Holzinger, M Kargl, B Kipperer, P Regitnig, M Plass, H Müller IEEE Access 10, 23732-23747, 2022 | 30 | 2022 |
| Explainability and causability in digital pathology M Plass, M Kargl, TR Kiehl, P Regitnig, C Geißler, T Evans, N Zerbe, ... The Journal of Pathology: Clinical Research 9 (4), 251-260, 2023 | 16 | 2023 |
| Pathologist validation of a machine learning–derived feature for colon cancer risk stratification V L’Imperio, E Wulczyn, M Plass, H Müller, N Tamini, L Gianotti, ... JAMA Network Open 6 (3), e2254891-e2254891, 2023 | 16 | 2023 |
| Lightweight distributed provenance model for complex real–world environments R Wittner, C Mascia, M Gallo, F Frexia, H Müller, M Plass, J Geiger, ... Scientific Data 9 (1), 503, 2022 | 13 | 2022 |
| A literature review on ethics for AI in biomedical research and biobanking M Kargl, M Plass, H Müller Yearbook of Medical Informatics 31 (01), 152-160, 2022 | 13 | 2022 |
| Privacy risks of whole-slide image sharing in digital pathology P Holub, H Müller, T Bíl, L Pireddu, M Plass, F Prasser, I Schlünder, ... Nature Communications 14 (1), 2577, 2023 | 11 | 2023 |
| Towards a taxonomy for explainable AI in computational pathology H Müller, M Kargl, M Plass, B Kipperer, L Brcic, P Regitnig, C Geißler, ... Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership …, 2022 | 6 | 2022 |
| Interactive machine learning (iml): a challenge for game-based approaches A Holzinger, M Plass, MD Kickmeier-Rust, I Guyon, E Viegas, S Escalera, ... Challenges in Machine Learning: Gaming and Education. NIPS Workshops, 2016 | 6 | 2016 |
| Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning JD Krogue, S Azizi, F Tan, I Flament-Auvigne, T Brown, M Plass, R Reihs, ... Communications Medicine 3 (1), 59, 2023 | 4 | 2023 |
| Human-AI interfaces are a central component of trustworthy AI M Plass, M Kargl, T Evans, L Brcic, P Regitnig, C Geißler, R Carvalho, ... Explainable AI: Foundations, Methodologies and Applications, 225-256, 2022 | 3 | 2022 |
| The common provenance model: Capturing distributed provenance in life sciences processes B Séroussi Challenges of Trustable AI and Added-Value on Health: Proceedings of MIE …, 2022 | 3 | 2022 |
