Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs.
Zijian ZhouBeatriz E. AdradaRosalind P. CandelariaNabil A. ElshafeeyMedine BogeRania M. MohamedSanaz PashapoorJia SunZhan XuBikash PanthiJong Bum SonMary S. GuirguisMiral M. PatelGary J. WhitmanTanya W. MoseleyMarion E. ScogginsJason B. WhiteJennifer K. LittonVincente ValeroKelly K. HuntDebu TripathyWei YangPeng WeiClinton YamMark D. PagelGaiane M. RauchJingfei MaPublished in: EMBC (2023)
Keyphrases
- deep learning
- cancer treatment
- decision support
- breast cancer
- unsupervised feature learning
- unsupervised learning
- machine learning
- dce mri
- mental models
- low grade
- magnetic resonance images
- deep architectures
- radiation therapy
- prostate cancer
- medical image analysis
- weakly supervised
- co occurrence
- computer aided diagnosis
- domain specific
- multiscale