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Embedding algorithms are increasingly used to represent clinical concepts in healthcare for improving machine learning tasks such as clinical phenotyping and disease prediction.
Pre-training of Graph Augmented Transformers for Medication Recommendation
Junyuan Shang, Tengfei Ma, Cao Xiao, and Jimeng Sun · 1906
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Time2Vec: Learning a Vector Representation of Time
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Temporal Self-Attention Network for Medical Concept Embedding
Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, and Michael Blumenstein · 1909
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Adam: A Method for Stochastic Optimization
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Learning Low-Dimensional Representations of Medical Concepts
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Early Detection of Heart Failure Using Electronic Health Records: Practical Implications for Time before Diagnosis, Data Diversity, Data Quantity and Data Density
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Clinical concept embeddings learned from massive sources of multimodal medical data
Andrew L. Beam, Benjamin Kompa, Allen Schmaltz, Inbar Fried, Grin Weber, Nathan Palmer, Xu Shi, Tianxi Cai, and Isaac S. Kohane · 2020
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A comprehensive EHR timeseries pre-training benchmark
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Recurrent Neural Networks for Multivariate Time Series with Missing Values
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Jinghe Zhang, Kamran Kowsari, James H. Harrison, Jennifer M. Lobo, and Laura E. Barnes · 2018
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