Article Versions Notes

Xu Z, Zhou Z, Son JB, Feng H, Adrada BE, Moseley TW, Candelaria RP, Guirguis MS, Patel MM, Whitman GJ, et al. Deep Learning Models Based on Pretreatment MRI and Clinicopathological Data to Predict Responses to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer. Cancers. 2025; 17(6):966. https://doi.org/10.3390/cancers17060966

Xu, Zhan, Zijian Zhou, Jong Bum Son, Haonan Feng, Beatriz E. Adrada, Tanya W. Moseley, Rosalind P. Candelaria, Mary S. Guirguis, Miral M. Patel, Gary J. Whitman, and et al. 2025. "Deep Learning Models Based on Pretreatment MRI and Clinicopathological Data to Predict Responses to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer" Cancers 17, no. 6: 966. https://doi.org/10.3390/cancers17060966

Xu, Z., Zhou, Z., Son, J. B., Feng, H., Adrada, B. E., Moseley, T. W., Candelaria, R. P., Guirguis, M. S., Patel, M. M., Whitman, G. J., Leung, J. W. T., Le-Petross, H. T. C., Mohamed, R. M., Panthi, B., Lane, D. L., Chen, H., Wei, P., Tripathy, D., Litton, J. K., ... Ma, J. (2025). Deep Learning Models Based on Pretreatment MRI and Clinicopathological Data to Predict Responses to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer. Cancers, 17(6), 966. https://doi.org/10.3390/cancers17060966