Information Extraction from Electronic Medical Records Using Multitask Recurrent Neural Network with Contextual Word Embedding
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Yuenan Liu | Minghui Qian | Jianliang Yang | Chenghua Guan | Xiangfei Yuan | Chenghua Guan | Yuenan Liu | Minghui Qian | Xiangfei Yuan | Jianliang Yang
[1] Carol Friedman,et al. Research Paper: A General Natural-language Text Processor for Clinical Radiology , 1994, J. Am. Medical Informatics Assoc..
[2] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[3] John F. Hurdle,et al. Extracting Information from Textual Documents in the Electronic Health Record: A Review of Recent Research , 2008, Yearbook of Medical Informatics.
[4] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..
[5] Xiaolong Wang,et al. Drug Name Recognition: Approaches and Resources , 2015, Inf..
[6] Alan R. Aronson,et al. An overview of MetaMap: historical perspective and recent advances , 2010, J. Am. Medical Informatics Assoc..
[7] Yoshua Bengio,et al. Random Search for Hyper-Parameter Optimization , 2012, J. Mach. Learn. Res..
[8] Ming Yang,et al. Entity recognition from clinical texts via recurrent neural network , 2017, BMC Medical Informatics and Decision Making.
[9] Abeed Sarker,et al. Portable automatic text classification for adverse drug reaction detection via multi-corpus training , 2015, J. Biomed. Informatics.
[10] Joel D. Martin,et al. Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010 , 2011, J. Am. Medical Informatics Assoc..
[11] David S. Wishart,et al. DrugBank 4.0: shedding new light on drug metabolism , 2013, Nucleic Acids Res..
[12] S. Hebbring. The challenges, advantages and future of phenome-wide association studies , 2014, Immunology.
[13] Maryam Habibi,et al. Deep learning with word embeddings improves biomedical named entity recognition , 2017, Bioinform..
[14] Hongfang Liu,et al. Journal of Biomedical Informatics , 2022 .
[15] I. Solti,et al. Developing and evaluating an automated appendicitis risk stratification algorithm for pediatric patients in the emergency department , 2013, Journal of the American Medical Informatics Association : JAMIA.
[16] David L Buckeridge,et al. Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol , 2015, Implementation Science.
[17] Chengjie Sun,et al. LSTM-CRF for Drug-Named Entity Recognition , 2017, Entropy.
[18] Sunghwan Sohn,et al. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications , 2010, J. Am. Medical Informatics Assoc..
[19] Peter Szolovits,et al. MIMIC-III, a freely accessible critical care database , 2016, Scientific Data.
[20] Hongfei Lin,et al. An attention‐based BiLSTM‐CRF approach to document‐level chemical named entity recognition , 2018, Bioinform..
[21] Massimo Piccardi,et al. Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition , 2017, J. Biomed. Informatics.
[22] Jingqi Wang,et al. Enhancing Clinical Concept Extraction with Contextual Embedding , 2019, J. Am. Medical Informatics Assoc..
[23] Shuying Shen,et al. 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text , 2011, J. Am. Medical Informatics Assoc..