mlsanityData to 14 Oct 2026

Generating patient cohorts from electronic health records using two-step retrieval-augmented text-to-SQL generation

arXiv 2502.21107 ↗First posted 28 Feb 2025cs.CLcited by 4

On the map: Retrieval-augmented generation → Medical and biomedical RAG

Abstract (arXiv)

Clinical cohort definition is crucial for patient recruitment and observational studies, yet translating inclusion/exclusion criteria into SQL queries remains challenging and manual. We present an automated system utilizing large language models that combines criteria parsing, two-level retrieval augmented generation with specialized knowledge bases, medical concept standardization, and SQL generation to retrieve patient cohorts with patient funnels. The system achieves 0.75 F1-score in cohort identification on EHR data, effectively capturing complex temporal and logical relationships. These results demonstrate the feasibility of automated cohort generation for epidemiological research.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 19 of its 43 references that are in the map. First posted on arXiv 28 Feb 2025.

Builds on

19 of 43 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Retrieval augmented text-to-SQL generation for epidemiological question answering using electronic health records14 Mar

Other references · 18

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  3. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 477
  4. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 385
  5. 2022Evaluating the Text-to-SQL Capabilities of Large Language Modelscited by 101
  6. 2019Text-to-SQL Generation for Question Answering on Electronic Medical Recordscited by 77
  7. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thoughtcited by 65
  8. 2023A Multi-Task Embedder For Retrieval Augmented LLMscited by 64
  9. 2023How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settingscited by 58
  10. 2024A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQLcited by 46
  11. 2023EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Recordscited by 45
  12. 2021Knowledge-Rich Self-Supervision for Biomedical Entity Linkingcited by 31
6 more
  1. 2023Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncologycited by 24
  2. 2023Selective Demonstrations for Cross-domain Text-to-SQLcited by 21
  3. 2023Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasetscited by 9
  4. 2023LeafAI: query generator for clinical cohort discovery rivaling a human programmercited by 9
  5. 2022Generalizing over Long Tail Concepts for Medical Term Normalizationcited by 8
  6. 2022Medical Coding with Biomedical Transformer Ensembles and Zero/Few-shot Learningcited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Studycited by 3
  2. 2026EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Recordscited by 0
  3. 2026ClinQueryAgent: A Conversational Agent for Population Health Managementcited by 0
  4. 2026Ascent: An Agentic System over the Model Context Protocol for Real-World Clinical Data Analysiscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Patient-Similarity Cohort Reasoning in Clinical Text-to-SQL
  2. 2025EMR-AGENT: Automating Cohort and Feature Extraction from EMR Databases
  3. 2026Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching
  4. 2026CBR-to-SQL: Rethinking Retrieval-based Text-to-SQL using Case-based Reasoning in the Healthcare Domain
  5. 2023CohortGPT: An Enhanced GPT for Participant Recruitment in Clinical Study
  6. 2026Harnessing Large Language Models for Precision Querying and Retrieval-Augmented Knowledge Extraction in Clinical Data Science
  7. 2023Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping
  8. 2025LLM-Match: An Open-Sourced Patient Matching Model Based on Large Language Models and Retrieval-Augmented Generation