Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials.
Andre EstevaJean FengDouwe van der WalShih-Cheng HuangJeffry P. SimkoSandy DevriesEmmalyn ChenEdward M. SchaefferTodd M. MorganYilun SunAmirata GhorbaniNikhil NaikDhruv NathawaniRichard SocherJeff M. MichalskiMack RoachThomas M. PisanskyJedidiah M. MonsonFarah NazJames WallaceMichelle J. FergusonJean-Paul BaharyJames ZouMatthew P. LungrenSerena YeungAshley E. RossMichael J. KucharczykLuis SouhamiLeslie BallasChristopher A. PetersSandy LiuAlexander G. BaloghPamela D. Randolph-JacksonDavid L. SchwartzMichael R. GirvigianNaoyuki G. SaitoAdam RabenRachel A. RabinovitchKhalil KatatoHoward M. SandlerPhuoc T. TranDaniel E. SprattStephanie PughFelix Y. FengOsama MohamadPublished in: npj Digit. Medicine (2022)
Keyphrases
- multi modal
- deep learning
- prostate cancer
- disease progression
- clinical trials
- cancer patients
- decision support system
- unsupervised learning
- mr images
- computer aided
- deformable registration
- image guided
- machine learning
- high dimensional
- imaging modalities
- experimental design
- medical image analysis
- data analysis
- magnetic resonance images
- data warehouse
- pattern recognition
- feature space
- data mining
- cross sectional
- x ray
- metadata
- computer vision
- image analysis