Hajri, R.; Aboudaram, C.; Lassau, N.; Assi, T.; Antoun, L.; Ribeiro, J.M.; Lacroix-Triki, M.; Ammari, S.; Balleyguier, C.
Prediction of Breast Cancer Response to Neoadjuvant Therapy with Machine Learning: A Clinical, MRI-Qualitative, and Radiomics Approach. Life 2025, 15, 1165.
https://doi.org/10.3390/life15081165
AMA Style
Hajri R, Aboudaram C, Lassau N, Assi T, Antoun L, Ribeiro JM, Lacroix-Triki M, Ammari S, Balleyguier C.
Prediction of Breast Cancer Response to Neoadjuvant Therapy with Machine Learning: A Clinical, MRI-Qualitative, and Radiomics Approach. Life. 2025; 15(8):1165.
https://doi.org/10.3390/life15081165
Chicago/Turabian Style
Hajri, Rami, Charles Aboudaram, Nathalie Lassau, Tarek Assi, Leony Antoun, Joana Mourato Ribeiro, Magali Lacroix-Triki, Samy Ammari, and Corinne Balleyguier.
2025. "Prediction of Breast Cancer Response to Neoadjuvant Therapy with Machine Learning: A Clinical, MRI-Qualitative, and Radiomics Approach" Life 15, no. 8: 1165.
https://doi.org/10.3390/life15081165
APA Style
Hajri, R., Aboudaram, C., Lassau, N., Assi, T., Antoun, L., Ribeiro, J. M., Lacroix-Triki, M., Ammari, S., & Balleyguier, C.
(2025). Prediction of Breast Cancer Response to Neoadjuvant Therapy with Machine Learning: A Clinical, MRI-Qualitative, and Radiomics Approach. Life, 15(8), 1165.
https://doi.org/10.3390/life15081165
