30 citations
- University of IowaUS8 papers
- Hanken School of EconomicsFI3 papers
- Nokia (Finland)FI3 papers
- Åbo Akademi UniversityFI2 papers
- Berlin Institute of Health at Charité - Universitätsmedizin BerlinDE2 papers
- Goethe University FrankfurtDE2 papers
- Ocean University of ChinaCN2 papers
- Seoul National UniversityKR2 papers
- Turku Centre for Computer ScienceFI2 papers
- University of CopenhagenDK2 papers
- Aalto UniversityFI1 paper
- Birmingham City UniversityGB1 paper
16 papers
Getting Ready for the EU AI Act in Healthcare. A call for Sustainable AI Development and Deployment
John Brandt Brodersen, Ilaria Amelia Caggiano, Pedro Kringen +6
Assessments of trustworthiness have become a cornerstone of responsible AI development. Especially in high-stakes fields like healthcare, aligning technical, evidence-based, and et…
How to Assess Trustworthy AI in Practice
Roberto V. Zicari, Julia Amann, Frédérick Bruneault +17
This report is a methodological reflection on Z-Inspection. Z-Inspection is a holistic process used to evaluate the trustworthiness of A…
Mislabel Detection of Finnish Publication Ranks
Anton Akusok, Mirka Saarela, Tommi Kärkkäinen +2
The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM). The purpose is to introduce and test recently propos…
Per-sample Prediction Intervals for Extreme Learning Machines
Anton Akusok, Yoan Miche, Kaj-Mikael Björk +1
Prediction intervals in supervised Machine Learning bound the region where the true outputs of new samples may fall. They are necessary in the task of separating reliable predictio…
Extreme Learning Tree
Anton Akusok, Emil Eirola, Kaj-Mikael Björk +1
The paper proposes a new variant of a decision tree, called an Extreme Learning Tree. It consists of an extremely random tree with non-linear data transformation, and a linear obse…
Spiking Networks for Improved Cognitive Abilities of Edge Computing Devices
Anton Akusok, Kaj-Mikael Björk, Leonardo Espinosa Leal +3
This concept paper highlights a recently opened opportunity for large scale analytical algorithms to be trained directly on edge devices. Such approach is a response to the arising…