Li, Ruijiang

A pathology foundation model for cancer diagnosis and prognosis prediction

Wang, X., Zhao, J., Marostica, E., Yuan, W., Jin, J., Zhang, J., Li, R., Tang, H., Wang, K., Li, Y., et al. (2024) · Nature

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 580

Development and Validation of an Individualized Immune Prognostic Signature in Early-Stage Nonsquamous Non–Small Cell Lung Cancer

Li, B., Cui, Y., Diehn, M., & Li, R. (2017) · JAMA Oncology

Lung Cancer Research StudiesBreast Cancer Treatment Studies

Cited by 514

A Vision-Language Foundation Model for Precision Oncology

Xiang, J., Wang, X., Zhang, X., Xi, Y., Eweje, F., Chen, Y., Li, Y., Bergstrom, C., Gopaulchan, M., Kim, T., et al. (2025) · Nature

AI in cancer detectionMultimodal Machine Learning Applications

Cited by 256

Development and Validation of a Deep Learning CT Signature to Predict Survival and Chemotherapy Benefit in Gastric Cancer: A Multicenter, Retrospective Study

Jiang, Y., Jin, C., Yu, H., Wu, J., Chen, C., Yuan, Q., Huang, W., Hu, Y., Xu, Y., Zhou, Z., et al. (2021) · Annals of Surgery

Radiomics and Machine Learning in Medical ImagingGastric Cancer Management and Outcomes

Cited by 169

Noninvasive imaging evaluation of tumor immune microenvironment to predict outcomes in gastric cancer

Jiang, Y., Wang, H., Wu, J., Chen, C., Yuan, Q., Huang, W., Li, T., Xi, S., Hu, Y., Zhou, Z., et al. (2020) · Annals of Oncology

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

Cited by 169

Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study

Saad, M. B., Hong, L., Aminu, M., Vokes, N. I., Chen, P., Salehjahromi, M., Qin, K., Sujit, S. J., Lu, X., Young, E., et al. (2023) · The Lancet Digital Health

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

Cited by 121

Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics

Jiang, Y., Zhou, K., Sun, Z., Wang, H., Xie, J., Zhang, T., Sang, S., Islam, M. T., Wang, J.-Y., Chen, C., et al. (2023) · Cell Reports Medicine

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

Cited by 120

Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study

Jiang, Y., Liang, X., Han, Z., Wang, W., Xi, S., Li, T., Chen, C., Yuan, Q., Li, N., Yu, J., et al. (2021) · The Lancet Digital Health

Radiomics and Machine Learning in Medical ImagingGastric Cancer Management and Outcomes

Cited by 58

Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer

Wu, J., Li, X., Teng, X., Rubin, D. L., Napel, S., Daniel, B. L., & Li, R. (2018) · Breast Cancer Research

MRI in cancer diagnosisRadiomics and Machine Learning in Medical Imaging

Cited by 53