mlsanityData to 14 Oct 2026

Prompt-based Extraction of Social Determinants of Health Using Few-shot Learning

arXiv 2306.07170 ↗First posted 12 Jun 2023cs.CLcited by 8

Not on the map. Why?

Abstract (arXiv)

Social determinants of health (SDOH) documented in the electronic health record through unstructured text are increasingly being studied to understand how SDOH impacts patient health outcomes. In this work, we utilize the Social History Annotation Corpus (SHAC), a multi-institutional corpus of de-identified social history sections annotated for SDOH, including substance use, employment, and living status information. We explore the automatic extraction of SDOH information with SHAC in both standoff and inline annotation formats using GPT-4 in a one-shot prompting setting. We compare GPT-4 extraction performance with a high-performing supervised approach and perform thorough error analyses. Our prompt-based GPT-4 method achieved an overall 0.652 F1 on the SHAC test set, similar to the 7th best-performing system among all teams in the n2c2 challenge with SHAC.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 12 of its 26 references that are in the map. First posted on arXiv 12 Jun 2023.

Builds on

12 of 26 references.

References · 12

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022Training language models to follow instructions with human feedbackcited by 15,971
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  4. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  5. 2022Can large language models reason about medical questions?cited by 194
  6. 2019Span-based Joint Entity and Relation Extraction with Transformer Pre-trainingcited by 133
  7. 2023DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4cited by 130
  8. 2021SciFive: a text-to-text transformer model for biomedical literaturecited by 99
  9. 2020Annotating Social Determinants of Health Using Active Learning, and Characterizing Determinants Using Neural Event Extractioncited by 32
  10. 2023The 2022 n2c2/UW Shared Task on Extracting Social Determinants of Healthcited by 21
  11. 2021A Study of Social and Behavioral Determinants of Health in Lung Cancer Patients Using Transformers-based Natural Language Processing Modelscited by 11
  12. 2022Leveraging Natural Language Processing to Augment Structured Social Determinants of Health Data in the Electronic Health Recordcited by 7

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 5; 2025: 1.

8 papers.

  1. 2023Large Language Models to Identify Social Determinants of Health in Electronic Health Recordscited by 55
  2. 2024Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysiscited by 10
  3. 2023Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Modelcited by 5
  4. 2024Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approachcited by 4
  5. 2024Adaptation of Biomedical and Clinical Pretrained Models to French Long Documents: A Comparative Studycited by 2
  6. 2024Exploring the Human-LLM Synergy in Advancing Theory-driven Qualitative Analysiscited by 2
  7. 2024CACER: Clinical Concept Annotations for Cancer Events and Relationscited by 2
  8. 2025Can Large Language Models Integrate Spatial Data? Empirical Insights into Reasoning Strengths and Computational Weaknessescited by 1