Federated Learning for Breast Density Classification: A Real-World Implementation.
Holger R. RothKen ChangPraveer SinghNir NeumarkWenqi LiVikash GuptaSharut GuptaLiangqiong QuAlvin IhsaniBernardo C. BizzoYuhong WenVarun BuchMeesam ShahFelipe KitamuraMatheus MendonçaVitor LavorAhmed HarouniColin CompasJesse TetreaultPrerna DograYan ChengSelnur ErdalRichard D. WhiteBehrooz HashemianThomas J. SchultzMiao ZhangAdam McCarthyB. Min YunElshaimaa SharafKatharina Viktoria HoebelJay B. PatelBryan ChenSean KoEvan LeibovitzEtta D. PisanoLaura CoombsDaguang XuKeith J. DreyerIttai DayanRam C. NaiduMona FloresDaniel L. RubinJayashree Kalpathy-CramerPublished in: DART/DCL@MICCAI (2020)
Keyphrases
- real world
- supervised learning
- learning systems
- learning algorithm
- automatic classification
- pattern recognition
- unsupervised learning
- learning phase
- incremental learning
- active learning
- data mining
- learning tasks
- multi category
- data sets
- discriminative learning
- pattern classification
- neural network
- machine learning
- learning process
- training set
- decision trees
- support vector machine
- digital libraries
- breast cancer diagnosis
- feature selection
- classification scheme
- feature extraction
- reinforcement learning
- computer aided
- classification rules
- decision rules
- knowledge acquisition
- text classification
- prior knowledge