Song, Andrew H.
Broad Institute · Harvard University · Dana-Farber Cancer Institute · Mass General Brigham
8 papers on CoChatORCID 0000-0001-9356-9156
Most cited papers
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Towards a general-purpose foundation model for computational pathology
Chen, R. J., Ding, T., Lu, M. Y., Williamson, D. F. K., Jaume, G., Song, A. H., Chen, B., Zhang, A., Shao, D., Shaban, M., et al. (2024) · Nature Medicine
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 1,560
- Verified
Artificial intelligence for digital and computational pathology
Song, A. H., Jaume, G., Williamson, D. F. K., Lu, M. Y., Vaidya, A., Miller, T. R., & Mahmood, F. (2023) · Nature Reviews Bioengineering
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 356
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A multimodal whole-slide foundation model for pathology
Ding, T., Wagner, S. J., Song, A. H., Chen, R. J., Lu, M. Y., Zhang, A., Vaidya, A. J., Jaume, G., Shaban, M., Kim, A., et al. (2025) · Nature Medicine
AI in cancer detectionMultimodal Machine Learning Applications
Cited by 171
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Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology
Song, A. H., Chen, R. J., Ding, T., Williamson, D. F. K., Jaume, G., & Mahmood, F. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 79
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Transcriptomics-Guided Slide Representation Learning in Computational Pathology
Jaume, G., Oldenburg, L., Vaidya, A., Chen, R. J., Williamson, D. F. K., Peeters, T., Song, A. H., & Mahmood, F. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 51
- Verified
Generative Artificial Intelligence in Anatomic Pathology
Brodsky, V., Ullah, E., Bychkov, A., Song, A. H., Walk, E. E., Louis, P., Rasool, G., Singh, R. S., Mahmood, F., Bui, M. M., et al. (2025) · Archives of Pathology & Laboratory Medicine
Artificial Intelligence in Healthcare and EducationAI in cancer detection
Cited by 48
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Incorporating Intratumoral Heterogeneity into Weakly-Supervised Deep Learning Models via Variance Pooling
Carmichael, I., Song, A. H., Chen, R. J., Williamson, D. F. K., Chen, T. Y., & Mahmood, F. (2022) · Lecture Notes in Computer Science
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 20
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Integrating context for superior cancer prognosis
Jaume, G., Song, A. H., & Mahmood, F. (2022) · Nature Biomedical Engineering
AI in cancer detectionRadiomics and Machine Learning in Medical Imaging
Cited by 8
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