Doctor AI: Predicting Clinical Events via Recurrent Neural Networks Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
Paper summary This paper presents an applications of RNNs to predict "clinical events", such as disease diagnosis and medication prescription and their timing. The paper proposes/suggests: 1. Applying an RNN to disease diagnosis, medication prescription and timing prediction. 2. "Initializing" the neural net with skipgrams instead of one-hot vectors. However, it seems from the description that the authors are not "initializing", rather just feeding a different feature vector into the RNN. 3. Initializing a model that is to be trained on a small corpus from a model trained on a large corpus works. Concludes: information can be transferred between models (read across hospitals).
arxiv.org
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Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
Choi, Edward and Bahadori, Mohammad Taha and Sun, Jimeng
arXiv e-Print archive - 2015 via Bibsonomy
Keywords: dblp


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