Haarburger, Christoph

Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI

Truhn, D., Schrading, S., Haarburger, C., Schneider, H., Merhof, D., & Kuhl, C. (2019) · Radiology

Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis

Cited by 273

Radiomics feature reproducibility under inter-rater variability in segmentations of CT images

Haarburger, C., Müller-Franzes, G., Weninger, L., Kuhl, C., Truhn, D., & Merhof, D. (2020) · Scientific Reports

Radiomics and Machine Learning in Medical ImagingMedical Image Segmentation Techniques

Cited by 139

Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers

Khader, F., Müller-Franzes, G., Wang, T., Han, T., Tayebi Arasteh, S., Haarburger, C., Stegmaier, J., Bressem, K., Kuhl, C., Nebelung, S., et al. (2023) · Radiology

Multimodal Machine Learning ApplicationsMachine Learning in Healthcare

Cited by 107

Medical large language models are susceptible to targeted misinformation attacks

Han, T., Nebelung, S., Khader, F., Wang, T., Müller-Franzes, G., Kuhl, C., Försch, S., Kleesiek, J., Haarburger, C., Bressem, K. K., et al. (2024) · npj Digital Medicine

Adversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education

Cited by 62

Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

Khader, F., Kather, J. N., Müller-Franzes, G., Wang, T., Han, T., Tayebi Arasteh, S., Hamesch, K., Bressem, K., Haarburger, C., Stegmaier, J., et al. (2023) · Scientific Reports

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 57