Chen, Tiffany Y.

Data-efficient and weakly supervised computational pathology on whole-slide images

Lu, M. Y., Williamson, D. F. K., Chen, T. Y., Chen, R. J., Barbieri, M., & Mahmood, F. (2021) · Nature Biomedical Engineering

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 2,282

Artificial intelligence for multimodal data integration in oncology

Lipkova, J., Chen, R. J., Chen, B., Lu, M. Y., Barbieri, M., Shao, D., Vaidya, A. J., Chen, C., Zhuang, L., Williamson, D. F. K., et al. (2022) · Cancer Cell

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

Cited by 777

Algorithmic fairness in artificial intelligence for medicine and healthcare

Chen, R. J., Wang, J. J., Williamson, D. F. K., Chen, T. Y., Lipkova, J., Lu, M. Y., Sahai, S., & Mahmood, F. (2023) · Nature Biomedical Engineering

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 750

Synthetic data in machine learning for medicine and healthcare

Chen, R. J., Lu, M. Y., Chen, T. Y., Williamson, D. F. K., & Mahmood, F. (2021) · Nature Biomedical Engineering

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 728

Pan-cancer integrative histology-genomic analysis via multimodal deep learning

Chen, R. J., Lu, M. Y., Williamson, D. F. K., Chen, T. Y., Lipkova, J., Noor, Z., Shaban, M., Shady, M., Williams, M., Joo, B., et al. (2022) · Cancer Cell

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 660

Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learning

Chen, R. J., Chen, C., Li, Y., Chen, T. Y., Trister, A. D., Krishnan, R. G., & Mahmood, F. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 621

Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images

Chen, R. J., Lu, M. Y., Weng, W.-H., Chen, T. Y., Williamson, D. F., Manz, T., Shady, M., & Mahmood, F. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 398

Federated learning for computational pathology on gigapixel whole slide images

Lu, M. Y., Chen, R. J., Kong, D., Lipkova, J., Singh, R., Williamson, D. F. K., Chen, T. Y., & Mahmood, F. (2022) · Medical Image Analysis

AI in cancer detectionPrivacy-Preserving Technologies in Data

Cited by 267

Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction Using Patch-Based Graph Convolutional Networks

Chen, R. J., Lu, M. Y., Shaban, M., Chen, C., Chen, T. Y., Williamson, D. F. K., & Mahmood, F. (2021) · Lecture Notes in Computer Science

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 176

Fast and scalable search of whole-slide images via self-supervised deep learning

Chen, C., Lu, M. Y., Williamson, D. F. K., Chen, T. Y., Schaumberg, A. J., & Mahmood, F. (2022) · Nature Biomedical Engineering

AI in cancer detectionImage Retrieval and Classification Techniques

Cited by 130

A deep-learning model for transforming the style of tissue images from cryosectioned to formalin-fixed and paraffin-embedded

Ozyoruk, K. B., Can, S., Darbaz, B., Başak, K., Demir, D., Gokceler, G. I., Serin, G., Hacisalihoglu, U. P., Kurtuluş, E., Lu, M. Y., et al. (2022) · Nature Biomedical Engineering

AI in cancer detectionGenerative Adversarial Networks and Image Synthesis

Cited by 86

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