Bressem, Keno K.

Current applications and challenges in large language models for patient care: a systematic review

Busch, F., Hoffmann, L., Rueger, C., van Dijk, E. H., Kader, R., Ortiz-Prado, E., Makowski, M. R., Saba, L., Hadamitzky, M., Kather, J. N., et al. (2025) · Communications Medicine

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 358

Leveraging gpt-4 for post hoc transformation of free-text radiology reports into structured reporting: a multilingual feasibility study

Adams, L. C., Truhn, D., Busch, F., Kader, A., Niehues, S. M., Makowski, M. R., & Bressem, K. K. (2023) · Radiology

Artificial Intelligence in Healthcare and EducationBiomedical Text Mining and Ontologies

Cited by 339

Large language models for structured reporting in radiology: past, present, and future

Busch, F., Hoffmann, L., dos Santos, D. P., Makowski, M. R., Saba, L., Prucker, P., Hadamitzky, M., Navab, N., Kather, J. N., Truhn, D., et al. (2024) · European Radiology

Artificial Intelligence in Healthcare and EducationRadiology practices and education

Cited by 134

Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients

Busch, F., Hoffmann, L., Xu, L., Zhang, L. J., Hu, B., García-Juárez, I., Toapanta-Yanchapaxi, L. N., Gorelik, N., Gorelik, V., Rodriguez-Granillo, G. A., et al. (2025) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 124

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

Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties

Busch, F., Hoffmann, L., Truhn, D., Ortiz-Prado, E., Makowski, M. R., Bressem, K. K., Adams, L. C., COMFORT Consortium, Abdala, N., Navarro, Á. A., et al. (2024) · BMC Medical Education

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 108

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

Biomedical Ethical Aspects Towards the Implementation of Artificial Intelligence in Medical Education

Busch, F., Adams, L. C., & Bressem, K. K. (2023) · Medical Science Educator

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 88

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

International pharmacy students' perceptions towards artificial intelligence in medicine—A multinational, multicentre cross‐sectional study

Busch, F., Hoffmann, L., Truhn, D., Palaian, S., Alomar, M., Shpati, K., Makowski, M. R., Bressem, K. K., & Adams, L. C. (2024) · British Journal of Clinical Pharmacology

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 80

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

Evaluating local open-source large language models for data extraction from unstructured reports on mechanical thrombectomy in patients with ischemic stroke

Meddeb, A., Ebert, P., Bressem, K. K., Desser, D., Dell'Orco, A., Bohner, G., Kleine, J. F., Siebert, E., Grauhan, N., Brockmann, M. A., et al. (2025) · Journal of NeuroInterventional Surgery

Machine Learning in HealthcareBiomedical Text Mining and Ontologies

Cited by 27

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

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

Mese, I., D’Antonoli, T. A., Bluethgen, C., Bressem, K., Cuocolo, R., Chaudhari, A., Tejani, A. S., Isaac, A., Ponsiglione, A., Meddeb, A., et al. (2026) · Diagnostic and Interventional Radiology

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 17

Agentic systems in radiology: Principles, opportunities, privacy risks, regulation, and sustainability concerns.

Tzanis, E., Adams, L. C., Akinci D’Antonoli, T., Bressem, K. K., Cuocolo, R., Kocak, B., Malamateniou, C., & Klontzas, M. E. (2026) · Diagnostic and Interventional Imaging

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 16

Evaluation of a retrieval-augmented generation-powered chatbot for pre-CT informed consent: a prospective comparative study

Busch, F., Kaibel, L., Nguyen, H., Lemke, T., Ziegelmayer, S., Graf, M., Marka, A. W., Endrös, L., Prucker, P., Spitzl, D., et al. (2025) · Journal of Imaging Informatics in Medicine

Artificial Intelligence in Healthcare and EducationPatient-Provider Communication in Healthcare

Cited by 10

LongHealth: A Question Answering Benchmark with Long Clinical Documents

Adams, L., Busch, F., Han, T., Excoffier, J.-B., Ortala, M., Löser, A., Aerts, H. J., Kather, J. N., Truhn, D., & Bressem, K. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 10

Beyond the vessel wall: single-cell dissection of epicardial fat–myocardial crosstalk in coronary artery disease

Puluca, N., Vafadarnejad, E., Saleem, T., Rammoser, C., Wirth, F., Schwerdt, V., Dreßen, M., Gottmann, I., Reiminger, X., Yan, Y., et al. (2026) · Cardiovascular Research

Cardiovascular Disease and AdiposityCardiac Fibrosis and Remodeling

Cited by 2

Improving Reliability and Explainability of Medical Question Answering through Atomic Fact Checking in Retrieval-Augmented LLMs

Vladika, J., Domres, A., Nguyen, M., Moser, R., Nano, J., Busch, F., Adams, L. C., Bressem, K. K., Bernhardt, D., Combs, S. E., et al. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationTopic Modeling

Cited by 1

GRASP: Gated Regression-Aware Skill Proposer for Self-Improving LLM Agents

Moll, J., Corbeil, J.-P., Pan, J., Hadamitzky, M., Rueckert, D., Adams, L., & Bressem, K. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence in Healthcare and Education

Cited by 0