Article Versions Notes

Lo Gullo R, Ochoa-Albiztegui RE, Chakraborty J, Thakur SB, Robson M, Jochelson MS, Varela K, Resch D, Eskreis-Winkler S, Pinker K. Development of an MRI Radiomic Machine-Learning Model to Predict Triple-Negative Breast Cancer Based on Fibroglandular Tissue of the Contralateral Unaffected Breast in Breast Cancer Patients. Cancers. 2024; 16(20):3480. https://doi.org/10.3390/cancers16203480

Lo Gullo, Roberto, Rosa Elena Ochoa-Albiztegui, Jayasree Chakraborty, Sunitha B. Thakur, Mark Robson, Maxine S. Jochelson, Keitha Varela, Daphne Resch, Sarah Eskreis-Winkler, and Katja Pinker. 2024. "Development of an MRI Radiomic Machine-Learning Model to Predict Triple-Negative Breast Cancer Based on Fibroglandular Tissue of the Contralateral Unaffected Breast in Breast Cancer Patients" Cancers 16, no. 20: 3480. https://doi.org/10.3390/cancers16203480

Lo Gullo, R., Ochoa-Albiztegui, R. E., Chakraborty, J., Thakur, S. B., Robson, M., Jochelson, M. S., Varela, K., Resch, D., Eskreis-Winkler, S., & Pinker, K. (2024). Development of an MRI Radiomic Machine-Learning Model to Predict Triple-Negative Breast Cancer Based on Fibroglandular Tissue of the Contralateral Unaffected Breast in Breast Cancer Patients. Cancers, 16(20), 3480. https://doi.org/10.3390/cancers16203480