641 citations · 714 across the 3 of their papers we have counts for
4 papers
What do we need to build explainable AI systems for the medical domain?
Andreas Holzinger, Chris Biemann, Constantinos S. Pattichis +1
Artificial intelligence (AI) generally and machine learning (ML) specifically demonstrate impressive practical success in many different application domains, e.g. in autonomous dri…
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology
Andreas Holzinger, Bernd Malle, Peter Kieseberg +4
Digital pathology is not only one of the most promising fields of diagnostic medicine, but at the same time a hot topic for fundamental research. Digital pathology is not just the…
Augmentor: An Image Augmentation Library for Machine Learning
Marcus D. Bloice, Christof Stocker, Andreas Holzinger
The generation of artificial data based on existing observations, known as data augmentation, is a technique used in machine learning to improve model accuracy, generalisation, and…
Review of Machine Learning Algorithms in Differential Expression Analysis
Irina Kuznetsova, Yuliya V Karpievitch, Aleksandra Filipovska +2
In biological research machine learning algorithms are part of nearly every analytical process. They are used to identify new insights into biological phenomena, interpret data, pr…