Using AI to improve data extraction from clinical notes in infectious diseases

SBIR TOPIC 135:Applying Large Language Models for Automated Entity Recognition, Relation Extraction/Ontology Metadata Enrichment from Free-Text Clinical Notes in Infectious/Immune-Mediated Diseases

NIH-funded research John Snow Labs INC · NIH-11214907

This study is working on smart computer programs that can quickly organize important information from doctors' notes about infections and immune diseases, making it easier for researchers to use this data and improve medical research.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionJohn Snow Labs INC NIH-funded
Lab location1 site (Lewes, United States)
Project IDNIH-11214907 on NIH RePORTER

What this research studies

This research focuses on developing advanced AI models to automate the extraction and standardization of metadata from unstructured clinical notes related to infectious and immune-mediated diseases. By leveraging state-of-the-art Natural Language Processing technology, the project aims to create efficient and accurate systems that can transform complex clinical data into structured formats. This will significantly reduce the time and expertise currently required for data management, making it easier for researchers to access and utilize important biomedical information. The ultimate goal is to enhance data sharing and improve the overall quality of biomedical research.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals affected by infectious or immune-mediated diseases whose clinical data can be utilized for metadata enrichment.

Not a fit: Patients with conditions unrelated to infectious or immune-mediated diseases may not receive any direct benefit from this research.

Why it matters

Potential benefit: If successful, this research could greatly enhance the efficiency and accuracy of biomedical data management, leading to improved research outcomes in infectious and immune-mediated diseases.

How similar studies have performed: Other research has shown success in utilizing AI and Natural Language Processing for data extraction in clinical settings, indicating a promising approach for this project.

Where this research is happening

Lewes, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions DiseaseDisorder
Last reviewed 2026-06-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.