Fu, Pingfu

Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer

Khorrami, M., Prasanna, P., Gupta, A., Patil, P., Velu, P. D., Thawani, R., Corredor, G., Alilou, M., Bera, K., Fu, P., et al. (2020) · Cancer Immunology Research

Radiomics and Machine Learning in Medical ImagingCancer Immunotherapy and Biomarkers

Cited by 297

CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction

Vaidya, P., Bera, K., Gupta, A., Wang, X., Corredor, G., Fu, P., Beig, N., Prasanna, P., Patil, P. D., Velu, P. D., et al. (2020) · The Lancet Digital Health

Radiomics and Machine Learning in Medical ImagingLung Cancer Diagnosis and Treatment

Cited by 134

Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors

Wang, X., Barrera, C., Bera, K., Viswanathan, V. S., Azarianpour-Esfahani, S., Koyuncu, C., Velu, P., Feldman, M. D., Yang, M., Fu, P., et al. (2022) · Science Advances

Cancer Immunotherapy and BiomarkersAI in cancer detection

Cited by 89

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics

Hoori, A., Al-Kindi, S., Hu, T., Song, Y., Wu, H., Lee, J., Tashtish, N., Fu, P., Gilkeson, R., Rajagopalan, S., et al. (2024) · Scientific Reports

Cardiac Imaging and DiagnosticsArtificial Intelligence in Healthcare

Cited by 31