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Biomedical data is inherently multimodal, comprising physical measurements and natural language narratives.
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Radiology objects in context (roco): a multimodal image dataset
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
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A dataset of clinically generated visual questions and answers about radiology images
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Mimic-cxr, a de-identified publicly available database of chest radiographs with free-text reports
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Huang, S.-C., Pareek, A., Seyyedi, S., Banerjee, I. & Lungren, M. P · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
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Zhang, Y., Jiang, H., Miura, Y., Manning, C. D. & Langlotz, C. P · 2020
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Achakulvisut, T., Acuna, D. & Kording, K · 2020
Beyond medical imaging-a review of multimodal deep learning in radiology (2022)
Heiliger, L., Sekuboyina, A., Menze, B., Egger, J. & Kleesiek, J · 2022
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Making the most of text semantics to improve biomedical vision–language processing
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Biogpt: generative pre-trained transformer for biomedical text generation and mining
Luo, R. et al · 2022
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Medical visual question answering via conditional reasoning
Zhan, L.-M., Liu, B., Fan, L., Chen, J. & Wu, X.-M · 2020
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Learning transferable visual models from natural language supervision
Radford, A. et al · 2021
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Zero-shot text-to-image generation
Ramesh, A. et al · 2021
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Multiple instance captioning: Learning representations from histopathology textbooks and articles
Gamper, J. & Rajpoot, N · 2021
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Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Changpinyo, S., Sharma, P., Ding, N. & Soricut, R · 2021
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Wit: Wikipedia-based image text dataset for multimodal multilingual machine learning
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Wang, Z., Wu, Z., Agarwal, D. & Sun, J · 2022
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Scaling language-image pre-training via masking
Li, Y., Fan, H., Hu, R., Feichtenhofer, C. & He, K · 2022
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Elevater: A benchmark and toolkit for evaluating language-augmented visual models
Li, C. et al · 2022
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An empirical study of training end-to-end vision-and-language transformers
Dou, Z.-Y. et al · 2022
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Joint learning of localized representations from medical images and reports
Müller, P., Kaissis, G., Zou, C. & Rueckert, D · 2022
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Self-supervised pretraining enables high-performance chest x-ray interpretation across clinical distributions
Iyer, N. S. et al · 2022
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Reproducible scaling laws for contrastive language-image learning
Cherti, M. et al · 2022
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Foundation models for generalist medical artificial intelligence
Moor, M. et al · 2023
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Towards generalist biomedical ai
Tu, T. et al · 2023
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Quilt-1m: One million image-text pairs for histopathology
Ikezogwo, W. O. et al · 2023
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Zhang, K. et al · 2023
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A visual–language foundation model for pathology image analysis using medical twitter
Huang, Z., Bianchi, F., Yuksekgonul, M., Montine, T. J. & Zou, J · 2023
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Medblip: Bootstrapping language-image pre-training from 3d medical images and texts
Chen, Q., Hu, X., Wang, Z. & Hong, Y · 2023
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Med-flamingo: a multimodal medical few-shot learner
Moor, M. et al · 2023
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A whole-slide foundation model for digital pathology from real-world data
Xu, H. et al · 2024
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Towards generalist biomedical ai
Tu, T. et al · 2024
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Llava-med: Training a large language-and-vision assistant for biomedicine in one day
Li, C. et al · 2024
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