ArticleAnnual review of biomedical data science2018
Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models.
Article in Annual review of biomedical data science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
137 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning natural language processing for identifying venous thromboembolism: systematic review and meta-analysis.Blood advances · 2024Pooled it
- Prevalence of Systemic Lupus Erythematosus in Australia, 2010-2022: A Population-Based Study Using Linked National Administrative Health Data.Arthritis care & research · 2026Article
- AI-based multimodal integration of genomics and electronic health records.Nature reviews. Genetics · 2026Review
- STDP-inspired temporal transition modeling for adaptive clinical risk prediction from electronic health records.medRxiv : the preprint server for health sciences · 2026Article
- Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort Study.Journal of medical Internet research · 2026Article
- Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping Algorithms.Research square · 2026Article
- Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping Algorithms.medRxiv : the preprint server for health sciences · 2026Article
- Machine learning in critical care: Improving prediction of mortality and intensive care unit stay after cardiac surgery.JTCVS open · 2026Article
- Drug Reaction with Eosinophilia and Systemic Symptoms in the Electronic Medical Record.International archives of allergy and immunology · 2026Article
- An LLM-assisted framework for accelerated and verifiable clinical hypothesis testing from electronic health records.medRxiv : the preprint server for health sciences · 2026Article
- A weakly supervised transformer for rare disease diagnosis and subphenotyping from EHRs with pulmonary case studies.NPJ digital medicine · 2026Article
- SHREC: A framework for advancing next-generation computational phenotyping with large language models.PLOS digital health · 2026Article
- Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.BMC medicine · 2026Article
- MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2026Article
- The Consistency of Hypercapnic Respiratory Failure Case Definitions in Electronic Health Record Data.Chest · 2026Article
- When algorithms infer gender: revisiting computational phenotyping with electronic health records data.Biology of sex differences · 2025Review
- Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity.BMC cardiovascular disorders · 2025Article
- Accuracy of Large Language Models to Identify Stroke Subtypes Within Unstructured Electronic Health Record Data.Stroke · 2025Article
- SHREC: A Framework for Advancing Next-Generation Computational Phenotyping with Large Language Models.ArXiv · 2025Article
- Transformer patient embedding using electronic health records enables patient stratification and progression analysis.NPJ digital medicine · 2025Article
77 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
With the widespread adoption of electronic health records (EHRs), large repositories of structured and unstructured patient data are becoming available to conduct observational studies. Finding patients with specific conditions or outcomes, known as phenotyping, is one of the most fundamental research problems encountered when using these new EHR data. Phenotyping forms the basis of translational research, comparative effectiveness studies, clinical decision support, and population health analyses using routinely collected EHR data. We review the evolution of electronic phenotyping, from the early rule-based methods to the cutting edge of supervised and unsupervised machine learning models. We aim to cover the most influential papers in commensurate detail, with a focus on both methodology and implementation. Finally, future research directions are explored.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.