A hybrid model combining case-based reasoning and fuzzy decision tree for medical data classification
By Chin-Yuan Fan, Pei-Chann Chang, Jyun-Jie Lin, Jui-Chien Hsieh. 2011
220 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sanjay Purushotham
- Yan Liu
- Zhengping Che
- Stan Matwin
- Xuan Liu
- Xiaoguang Wang
- Robinder G. Khemani
- David C. Kale
In Computational Theory and Mathematics
In Information Systems
- Sanjay Purushotham
- Stan Matwin
- Zhengping Che
- Robinder G. Khemani
- Yan Liu
- Hao Wang
- Dit-Yan Yeung
- Wu-Jun Li
Citations in the corpus
- Distilling Knowledge from Deep Networks with Applications to Healthcare Domain (2015, background): “Decision trees [36] - due to their easy interpretability - have been quite successfully employed in the healthcare domain [6, 45, 14] and clinicians have embraced it to make informed decisions.”
- Improving the Interpretability of Deep Neural Networks with Knowledge Distillation (2018, background): “For instance, decision trees are preferred over DNN in the health care domain for disease diagnosis due to their ease of interpretation [1] [2] [3].”
- Interpretable Deep Models for ICU Outcome Prediction (2016, methodology): “Decision trees 14 , due to their ease of interpretation, have been successfully employed in the health care domain 15,16,17 , and clinicians have embraced them for predictive tasks such as disease diagnosis.”