A hierarchical deep learning approach with transparency and interpretability based on small samples for glaucoma diagnosis.
Yongli XuMan HuHanruo LiuHao YangHuaizhou WangShuai LuTianwei LiangXiaoxing LiMai XuLiu LiHuiqi LiXin JiZhijun WangLi LiRobert N. WeinrebNingli WangPublished in: npj Digit. Medicine (2021)
Keyphrases
- deep learning
- small samples
- unsupervised learning
- restricted boltzmann machine
- deep belief networks
- sample size
- model selection
- unsupervised feature learning
- feature selection
- optic nerve
- machine learning
- accurate models
- mental models
- regression trees
- support vector machine
- prediction accuracy
- upper bound
- natural images
- feature space
- neural network