Kaczmarczyk, Robert

LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs

Schuhmann, C., Vencu, R., Beaumont, R., Kaczmarczyk, R., Mullis, C., Katta, A., Coombes, T., Jitsev, J., & Komatsuzaki, A. (2021) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 358

LAION-5B: An Open Large-Scale Dataset for Training Next Generation Image-Text Models

Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., et al. (2022) · Advances in Neural Information Processing Systems 35

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 325

Perceptions of Digital Health Education Among European Medical Students: Mixed Methods Survey

Machleid, F., Kaczmarczyk, R., Johann, D., Balčiūnas, J., Atienza-Carbonell, B., von Maltzahn, F., & Mosch, L. (2020) · Journal of Medical Internet Research

Innovations in Medical EducationDigital literacy in education

Cited by 190

Artificial Intelligence in Medical Education: Comparative Analysis of ChatGPT, Bing, and Medical Students in Germany

Roos, J., Kasapovic, A., Jansen, T., & Kaczmarczyk, R. (2023) · JMIR Medical Education

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Education

Cited by 98

Generating dermatopathology reports from gigapixel whole slide images with HistoGPT

Tran, M., Schmidle, P., Guo, R. R., Wagner, S. J., Koch, V., Lupperger, V., Novotny, B., Murphree, D. H., Hardway, H. D., D’Amato, M., et al. (2025) · Nature Communications

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 36