no code implementations • 23 Mar 2023 • Petra Heck, Gerard Schouten
A production-ready AI system needs to be trustworthy, i. e. of high quality.
1 code implementation • 27 Jul 2021 • Ralf Raumanns, Gerard Schouten, Max Joosten, Josien P. W. Pluim, Veronika Cheplygina
In this paper we first analyse the correlations between the annotations and the diagnostic label of the lesion, as well as study the agreement between different annotation sources.
no code implementations • 19 Mar 2021 • Petra Heck, Gerard Schouten
The experience with this programme and the practical assignments our students execute in industry has given us valuable insights on the profession of AI engineer.
no code implementations • 3 Nov 2020 • Petra Heck, Gerard Schouten
In industry as well as education as well as academics we see a growing need for knowledge on how to apply machine learning in software applications.
no code implementations • 20 May 2020 • Samaneh Abbasi-Sureshjani, Ralf Raumanns, Britt E. J. Michels, Gerard Schouten, Veronika Cheplygina
Surprisingly, we found that papers focusing on diagnosis rarely describe the demographics of the datasets used, and the diagnosis is purely based on images.
1 code implementation • 28 Apr 2020 • Ralf Raumanns, Elif K Contar, Gerard Schouten, Veronika Cheplygina
Machine learning has a recognised need for large amounts of annotated data.