Predicting high-risk prognosis from diagnostic histories of adult disease patients via deep recurrent neural networks.
Jung-Woo HaAdrian KimDongwon KimJeonghee KimJeong-Whun KimJin Joo ParkBorim RyuPublished in: BigComp (2017)
Keyphrases
- high risk
- recurrent neural networks
- chronic disease
- early diagnosis
- prostate cancer
- disease diagnosis
- diagnostic tool
- prognostic factors
- patient groups
- risk factors
- autism spectrum disorder
- cancer patients
- breast cancer
- lung cancer
- early detection
- breast cancer patients
- neural network
- feed forward
- clinically relevant
- diagnostic process
- recurrent networks
- echo state networks
- artificial neural networks
- computer aided
- medical practitioners
- fault diagnosis
- expert systems
- reservoir computing
- cardiovascular disease
- intensive care unit
- mr images
- medical doctors
- outcome prediction
- nonlinear dynamic systems
- image registration
- genetic algorithm
- machine learning
- blood pressure
- decision support system
- decision making