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Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

arXiv 1511.05942 ↗First posted 18 Nov 2015cs.LGcited by 208

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Abstract (arXiv)

Leveraging large historical data in electronic health record (EHR), we developed Doctor AI, a generic predictive model that covers observed medical conditions and medication uses. Doctor AI is a temporal model using recurrent neural networks (RNN) and was developed and applied to longitudinal time stamped EHR data from 260K patients over 8 years. Encounter records (e.g. diagnosis codes, medication codes or procedure codes) were input to RNN to predict (all) the diagnosis and medication categories for a subsequent visit. Doctor AI assesses the history of patients to make multilabel predictions (one label for each diagnosis or medication category). Based on separate blind test set evaluation, Doctor AI can perform differential diagnosis with up to 79% recall@30, significantly higher than several baselines. Moreover, we demonstrate great generalizability of Doctor AI by adapting the resulting models from one institution to another without losing substantial accuracy.

Key facts. Cited by 208 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Nov 2015.

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Citing papers per year: 2021: 48; 2022: 25; 2023: 37; 2024: 33; 2025: 31; 2026: 34.

208 papers.

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  1. 2021Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunitiescited by 125
  2. 2021Time Series Prediction using Deep Learning Methods in Healthcarecited by 74
  3. 2021Characterizing Fairness Over the Set of Good Models Under Selective Labelscited by 65
  4. 2023GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphscited by 58
  5. 2021SafeDrug: Dual Molecular Graph Encoders for Recommending Effective and Safe Drug Combinationscited by 54
  6. 2021Hi-BEHRT: Hierarchical Transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health recordscited by 54
  7. 2022PLM-ICD: Automatic ICD Coding with Pretrained Language Modelscited by 49
  8. 2023Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Eventscited by 46
  9. 2024A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicinecited by 45
  10. 2022GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learningcited by 36
  11. 2024Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Datacited by 36
  12. 2021Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Reviewcited by 35
38 more
  1. 2021Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologiescited by 34
  2. 2022Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modelingcited by 33
  3. 2021Heterogeneous Similarity Graph Neural Network on Electronic Health Recordscited by 30
  4. 2021MUFASA: Multimodal Fusion Architecture Search for Electronic Health Recordscited by 30
  5. 2021Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcarecited by 30
  6. 2023The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRscited by 29
  7. 2021How to Leverage Multimodal EHR Data for Better Medical Predictions?cited by 26
  8. 2022A Unified Review of Deep Learning for Automated Medical Codingcited by 26
  9. 2021Towards BERT-based Automatic ICD Coding: Limitations and Opportunitiescited by 25
  10. 2021Unifying Heterogeneous Electronic Health Records Systems via Text-Based Code Embeddingcited by 24
  11. 2024TWIN-GPT: Digital Twins for Clinical Trials via Large Language Modelcited by 24
  12. 2022PromptEHR: Conditional Electronic Healthcare Records Generation with Prompt Learningcited by 22
  13. 2021Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphscited by 20
  14. 2024CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRTcited by 20
  15. 2025Comprehensive Review of Neural Differential Equations for Time Series Analysiscited by 20
  16. 2021Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Predictioncited by 15
  17. 2022Multimodal data matters: language model pre-training over structured and unstructured electronic health recordscited by 13
  18. 2022SurvLatent ODE : A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) predictioncited by 13
  19. 2023Event-Based Contrastive Learning for Medical Time Seriescited by 13
  20. 2021Neural Pharmacodynamic State Space Modelingcited by 12
  21. 2021Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classificationcited by 12
  22. 2023ExBEHRT: Extended Transformer for Electronic Health Records to Predict Disease Subtypes & Progressionscited by 12
  23. 2023Clairvoyance: A Pipeline Toolkit for Medical Time Seriescited by 12
  24. 2024Recent Advances in Predictive Modeling with Electronic Health Recordscited by 11
  25. 2025Explainability in Practice: A Survey of Explainable NLP Across Various Domainscited by 11
  26. 2025Foundation models for electronic health records: representation dynamics and transferabilitycited by 11
  27. 2022A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Carecited by 10
  28. 2021An Explainable CNN Approach for Medical Codes Prediction from Clinical Textcited by 9
  29. 2023Synthetic Data in Healthcarecited by 8
  30. 2024TimEHR: Image-based Time Series Generation for Electronic Health Recordscited by 8
  31. 2022Determinantal Point Process Likelihoods for Sequential Recommendationcited by 7
  32. 2022On Efficient Approximate Queries over Machine Learning Modelscited by 7
  33. 2023Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Modelscited by 7
  34. 2024CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health statecited by 7
  35. 2024TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Datacited by 7
  36. 2024Neuro-Symbolic AI for Military Applicationscited by 7
  37. 2025Structured Semantics from Unstructured Notes: Language Model Approaches to EHR-Based Decision Supportcited by 7
  38. 2022Artificial Intelligence for In Silico Clinical Trials: A Reviewcited by 6

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