Kather, Jakob Nikolas

Regression-based Deep-Learning predicts molecular biomarkers from pathology slides

El Nahhas, O. S. M., Loeffler, C. M. L., Carrero, Z. I., van Treeck, M., Kolbinger, F. R., Hewitt, K. J., Muti, H. S., Graziani, M., Zeng, Q., Calderaro, J., et al. (2024) · Nature Communications

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 108

End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study

Jiang, X., Hoffmeister, M., Brenner, H., Muti, H. S., Yuan, T., Foersch, S., West, N. P., Brobeil, A., Jonnagaddala, J., Hawkins, N., et al. (2024) · The Lancet Digital Health

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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

Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification

Höhn, J., Krieghoff-Henning, E., Jutzi, T. B., von Kalle, C., Utikal, J. S., Meier, F., Gellrich, F. F., Hobelsberger, S., Hauschild, A., Schlager, J. G., et al. (2021) · European Journal of Cancer

AI in cancer detectionCutaneous Melanoma Detection and Management

Cited by 106

Large language models should be used as scientific reasoning engines, not knowledge databases

Truhn, D., Reis-Filho, J. S., & Kather, J. N. (2023) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 102

New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

Derraz, B., Breda, G., Kaempf, C., Baenke, F., Cotte, F., Reiche, K., Köhl, U., Kather, J. N., Eskenazy, D., & Gilbert, S. (2024) · npj Precision Oncology

Artificial Intelligence in Healthcare and EducationBiomedical Ethics and Regulation

Cited by 94

GPT-4 for Information Retrieval and Comparison of Medical Oncology Guidelines

Ferber, D., Wiest, I. C., Wölflein, G., Ebert, M. P., Beutel, G., Eckardt, J.-N., Truhn, D., Springfeld, C., Jäger, D., & Kather, J. N. (2024) · NEJM AI

Artificial Intelligence in Healthcare and EducationClinical practice guidelines implementation

Cited by 92

Benchmarking foundation models as feature extractors for weakly supervised computational pathology

Neidlinger, P., El Nahhas, O. S. M., Muti, H. S., Lenz, T., Hoffmeister, M., Brenner, H., van Treeck, M., Langer, R., Dislich, B., Behrens, H. M., et al. (2025) · Nature Biomedical Engineering

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 80

Overcoming the challenges to implementation of artificial intelligence in pathology

Reis-Filho, J. S., & Kather, J. N. (2023) · JNCI: Journal of the National Cancer Institute

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 79

Large language models and multimodal foundation models for precision oncology

Truhn, D., Eckardt, J.-N., Ferber, D., & Kather, J. N. (2024) · npj Precision Oncology

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 79

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

Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists

Brinker, T. J., Schmitt, M., Krieghoff-Henning, E. I., Barnhill, R., Beltraminelli, H., Braun, S. A., Carr, R., Fernandez-Figueras, M.-T., Ferrara, G., Fraitag, S., et al. (2022) · Journal of the American Academy of Dermatology

AI in cancer detectionCutaneous Melanoma Detection and Management

Cited by 70

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

Skeletal Muscle Composition Predicts Outcome in Critically Ill Patients

Loosen, S. H., Schulze-Hagen, M., Püngel, T., Bündgens, L., Wirtz, T., Kather, J. N., Vucur, M., Paffenholz, P., Demir, M., Bruners, P., et al. (2020) · Critical Care Explorations

Nutrition and Health in AgingClinical Nutrition and Gastroenterology

Cited by 58

Effects of Label Noise on Deep Learning-Based Skin Cancer Classification

Hekler, A., Kather, J. N., Krieghoff-Henning, E., Utikal, J. S., Meier, F., Gellrich, F. F., Upmeier zu Belzen, J., French, L., Schlager, J. G., Ghoreschi, K., et al. (2020) · Frontiers in Medicine

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 58

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

Use of artificial intelligence for liver diseases: A survey from the EASL congress 2024

Žigutytė, L., Sorz-Nechay, T., Clusmann, J., & Kather, J. N. (2024) · JHEP Reports

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

Cited by 33

The ecological footprint of medical AI

Truhn, D., Müller-Franzes, G., & Kather, J. N. (2023) · European Radiology

Green IT and SustainabilityArtificial Intelligence in Healthcare and Education

Cited by 32

Overcoming regulatory barriers to the implementation of AI agents in healthcare

Freyer, O., Jayabalan, S., Kather, J. N., & Gilbert, S. (2025) · Nature Medicine

Artificial Intelligence in Healthcare and EducationHealthcare Regulation

Cited by 31

Large language models as a diagnostic support tool in neuropathology

Hewitt, K. J., Wiest, I. C., Carrero, Z. I., Bejan, L., Millner, T. O., Brandner, S., & Kather, J. N. (2024) · The Journal of Pathology: Clinical Research

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 27

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression

Ligero, M., Serna, G., El Nahhas, O. S. M., Sansano, I., Mauchanski, S., Viaplana, C., Calderaro, J., Toledo, R. A., Dienstmann, R., Vanguri, R. S., et al. (2024) · Cancer Research Communications

AI in cancer detectionCancer Immunotherapy and Biomarkers

Cited by 22

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

LLM Agents Making Agent Tools

Wölflein, G., Ferber, D., Truhn, D., Arandjelovic, O., & Kather, J. N. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 16