Nebelung, Sven

An MRI deep learning model predicts outcome in rectal cancer

Jiang, X., Zhao, H., Saldanha, O. L., Nebelung, S., Kuhl, C., Amygdalos, I., Lang, S. A., Wu, X., Meng, X., Truhn, D., et al. (2023) · Radiology

Radiomics and Machine Learning in Medical ImagingColorectal Cancer Surgical Treatments

Cited by 127

Extracting structured information from unstructured histopathology reports using generative pre‐trained transformer 4 ( GPT ‐4)

Truhn, D., Loeffler, C. M., Müller‐Franzes, G., Nebelung, S., Hewitt, K. J., Brandner, S., Bressem, K. K., Foersch, S., & Kather, J. N. (2024) · The Journal of Pathology

Artificial Intelligence in Healthcare and EducationAI in cancer detection

Cited by 124

Large language models streamline automated machine learning for clinical studies

Tayebi Arasteh, S., Han, T., Lotfinia, M., Kuhl, C., Kather, J. N., Truhn, D., & Nebelung, S. (2024) · Nature Communications

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 114

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

Comparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions

Han, T., Adams, L. C., Bressem, K. K., Busch, F., Nebelung, S., & Truhn, D. (2024) · JAMA

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 83

A pilot study on the efficacy of GPT-4 in providing orthopedic treatment recommendations from MRI reports

Truhn, D., Weber, C. D., Braun, B. J., Bressem, K., Kather, J. N., Kuhl, C., & Nebelung, S. (2023) · Scientific Reports

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 71

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

Multimodal Large Language Models are Generalist Medical Image Interpreters

Han, T., Adams, L. C., Nebelung, S., Kather, J. N., Bressem, K. K., & Truhn, D. (2023) · medRxiv

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 18