Explainable and Actionable Machine Learning Models for Electronic Health Record Data
暂无分享，去创建一个
[1] J V Tu,et al. Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. , 1996, Journal of clinical epidemiology.
[2] Jeffrey Dean,et al. Scalable and accurate deep learning with electronic health records , 2018, npj Digital Medicine.
[3] David Sontag,et al. Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests , 2016, MLHC.
[4] Charles Elkan,et al. Learning to Diagnose with LSTM Recurrent Neural Networks , 2015, ICLR.
[5] John J. Bartholdi,et al. Single transferable vote resists strategic voting , 2015 .
[6] Christian Biemann,et al. What do we need to build explainable AI systems for the medical domain? , 2017, ArXiv.
[7] Anne E Carpenter,et al. Opportunities and obstacles for deep learning in biology and medicine , 2017, bioRxiv.
[8] Scott Lundberg,et al. A Unified Approach to Interpreting Model Predictions , 2017, NIPS.
[9] Carlos Guestrin,et al. "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.
[10] Byron C. Wallace,et al. Attention is not Explanation , 2019, NAACL.
[11] Amina Adadi,et al. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI) , 2018, IEEE Access.