406 citations · 661 across the 8 of their papers we have counts for
8 papers
When Excellence Stops Producing Knowledge: A Practitioner's Observation on Research Funding
Heimo Müller
After almost four decades of participating in competitive research funding -- as applicant, coordinator, evaluator, and panel member -- I have come to see a structural paradox: man…
Diffusion-based generation of Histopathological Whole Slide Images at a Gigapixel scale
Robert Harb, Thomas Pock, Heimo Müller
We present a novel diffusion-based approach to generate synthetic histopathological Whole Slide Images (WSIs) at an unprecedented gigapixel scale. Synthetic WSIs have many potentia…
Ethical ChatGPT: Concerns, Challenges, and Commandments
Jianlong Zhou, Heimo Müller, Andreas Holzinger +1
Large language models, e.g. ChatGPT are currently contributing enormously to make artificial intelligence even more popular, especially among the general population. However, such…
Recommendations on test datasets for evaluating AI solutions in pathology
André Homeyer, Christian Geißler, Lars Ole Schwen +27
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to…
The FeatureCloud AI Store for Federated Learning in Biomedicine and Beyond
Julian Matschinske, Julian Späth, Reza Nasirigerdeh +29
Machine Learning (ML) and Artificial Intelligence (AI) have shown promising results in many areas and are driven by the increasing amount of available data. However, this data is o…
Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading
Ellery Wulczyn, Kunal Nagpal, Matthew Symonds +20
Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial i…
Measuring the Quality of Explanations: The System Causability Scale (SCS). Comparing Human and Machine Explanations
Andreas Holzinger, André Carrington, Heimo Müller
Recent success in Artificial Intelligence (AI) and Machine Learning (ML) allow problem solving automatically without any human intervention. Autonomous approaches can be very conve…
Kandinsky Patterns
Heimo Mueller, Andreas Holzinger
Kandinsky Figures and Kandinsky Patterns are mathematically describable, simple self-contained hence controllable test data sets for the development, validation and training of exp…