Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.
Cain, Elizabeth Hope
Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set. [electronic resource] - Breast cancer research and treatment Jan 2019 - 455-463 p. digital
Publication Type: Journal Article; Validation Study
1573-7217
10.1007/s10549-018-4990-9 doi
Adult
Aged
Antineoplastic Combined Chemotherapy Protocols--therapeutic use
Breast--diagnostic imaging
Feasibility Studies
Female
Humans
Image Processing, Computer-Assisted--methods
Machine Learning
Magnetic Resonance Imaging
Mastectomy, Segmental
Middle Aged
Neoadjuvant Therapy--methods
Neoplasm Staging
ROC Curve
Receptor, ErbB-2--metabolism
Retrospective Studies
Treatment Outcome
Triple Negative Breast Neoplasms--diagnostic imaging
Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set. [electronic resource] - Breast cancer research and treatment Jan 2019 - 455-463 p. digital
Publication Type: Journal Article; Validation Study
1573-7217
10.1007/s10549-018-4990-9 doi
Adult
Aged
Antineoplastic Combined Chemotherapy Protocols--therapeutic use
Breast--diagnostic imaging
Feasibility Studies
Female
Humans
Image Processing, Computer-Assisted--methods
Machine Learning
Magnetic Resonance Imaging
Mastectomy, Segmental
Middle Aged
Neoadjuvant Therapy--methods
Neoplasm Staging
ROC Curve
Receptor, ErbB-2--metabolism
Retrospective Studies
Treatment Outcome
Triple Negative Breast Neoplasms--diagnostic imaging