6 papers
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…
The Impact of Preprocessing Methods on Racial Encoding and Model Robustness in CXR Diagnosis
Dishantkumar Sutariya, Eike Petersen
Deep learning models can identify racial identity with high accuracy from chest X-ray (CXR) recordings. Thus, there is widespread concern about the potential for racial shortcut le…
meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis
Dishantkumar Sutariya, Eike Petersen
Analyzing machine learning model performance stratified by patient and recording properties is becoming the accepted norm and often yields crucial insights about important model fa…
Onto-Epistemological Analysis of AI Explanations
Martina Mattioli, Eike Petersen, Aasa Feragen +2
Artificial intelligence (AI) is being applied in almost every field. At the same time, the currently dominant deep learning methods are fundamentally black-box systems that lack ex…
Robustness and sex differences in skin cancer detection: logistic regression vs CNNs
Nikolette Pedersen, Regitze Sydendal, Andreas Wulff +3
Deep learning has been reported to achieve high performances in the detection of skin cancer, yet many challenges regarding the reproducibility of results and biases remain. This s…
Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis using Slice Discovery Methods
Vincent Olesen, Nina Weng, Aasa Feragen +1
Machine learning models have achieved high overall accuracy in medical image analysis. However, performance disparities on specific patient groups pose challenges to their clinical…