14 papers
Data Annotations as Pedagogical Hints: From Subjective Labels to Critical Thinking
Ralf Raumanns, Theresa Elstner, Louis Ferger-Andrews +5
Machine learning courses often use pre-labeled datasets, hiding the subjectivity of human annotation. This creates students with an overly trusting view of AI data and models, unde…
Surgical Anatomy Recognition with Context Learning using Foundation Representations
Ronald L. P. D. de Jong, Tim J. M. Jaspers, Raf A. H. Vervoort +9
Accurate recognition of anatomical structures is essential for safe and effective minimally invasive surgery (MIS), yet it remains underexplored in surgical computer vision due to…
Object Tokens as a Bridge Between Segmentation and Visual Question Answering in Robotic Surgery
Yiping Li, Ronald de Jong, Romy van Jaarsveld +5
Visual Question Answering (VQA) in robotic surgery, referred to as surgical VQA, requires high-level understanding of complex surgical scenes and the integration of visual percepti…
Effect of Demographic Bias on Skin Lesion Classification
Ralf Raumanns, Gerard Schouten, Veronika Cheplygina +1
In this study, we evaluate the performance of skin lesion classification using ResNet-based convolutional models, focusing on the impact of demographic bias in training data, parti…
Attention-Based Multimodal Survival Prediction with Cross-Modal Bilinear Fusion
Hassan Keshvarikhojasteh, Josien P. W. Pluim, Mitko Veta
We propose a novel multimodal deep learning framework for patient-level survival prediction, which integrates whole-slide histology features, RNA-seq expression profiles, and clini…
Beyond accuracy: quantifying the reliability of Multiple Instance Learning for Whole Slide Image classification
Hassan Keshvarikhojasteh, Marc Aubreville, Christof A. Bertram +2
Machine learning models have become integral to many fields, but their reliability, defined as producing dependable, trustworthy, and domain-consistent predictions, remains a criti…