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Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records., , , , and . CoRR, (2020)Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions., , , , , , , , , and 5 other author(s). AIME, volume 12299 of Lecture Notes in Computer Science, page 14-25. Springer, (2020)Extracting Social Isolation Information From Psychiatric Notes in the Electronic Health Records., , , , , , , , , and 4 other author(s). AMIA, AMIA, (2021)Time Aggregation and Model Interpretation for Deep Multivariate Longitudinal Patient Outcome Forecasting Systems in Chronic Ambulatory Care., , , and . CoRR, (2018)Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning., , , , , , , , and . CoRR, (2023)Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning., , , , , , , , and . MLMI@MICCAI, volume 13583 of Lecture Notes in Computer Science, page 11-20. Springer, (2022)A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19., , , , , , , and . Artif. Intell. Medicine, (2024)Deep Learning Predicts Hip Fracture using Confounding Patient and Healthcare Variables., , , , , , , , , and . CoRR, (2018)Automatic processing of Electronic Medical Records using Deep Learning., , , , , and . PervasiveHealth, page 251-257. ACM, (2018)Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale., , , , , , , , and . CoRR, (2020)