RF1AG072799

Facilitate Observational Studies of Alzheimer's Disease and Alzheimer's Disease-Related Dementias Using Ontology and Natural Language Processing - Project Summary

As the 6th leading cause of death in the US, Alzheimer's Disease (AD) and Alzheimer's Disease-Related Dementias (ADRD) affect about 5.7 million Americans. However, up until now, our understanding of risk factors of AD/ADRD is still limited and our efforts on developing effective treatments for AD/ADRD have been greatly disappointing. Therefore, there is an urgent need to develop new methods to conduct AD/ADRD research more efficiently.

One of the potential approaches is to leverage large, longitudinal, observational clinical data accumulated in electronic health records (EHRs). Nevertheless, current uses of EHRs for AD/ADRD research is very limited, often requiring manual data extraction and normalization (i.e., manual chart review), which is labor-intensive and time-consuming.

Therefore, in this study, we plan to develop novel ontology and natural language processing (NLP) based informatics methods and tools to automatically extract and normalize AD/ADRD-related clinical data in EHRs, thus facilitating efficient AD/ADRD observational studies using EHRs.

We propose the following three specific aims to achieve this goal:

1) Build an information model for EHR-based AD/ADRD research using a formal ontology representation approach.

2) Extract and normalize AD/ADRD information in clinical documents using NLP technologies.

3) Evaluate developed informatics methods and tools through demonstration studies and disseminate them to support observational AD/ADRD research.

Yale Univ

NOT APPLICABLE

93.866 - Aging Research

National Institute on Aging (NIA) [HHS - NIH]

New Haven, Connecticut 065103210 United States

Single Zip Code

Change of Recipient Organization (Type 7 Parent Clinical Trial Optional) (PA-21-268)

Amendment Since initial award the End Date has been extended from 04/30/24 to 04/30/25.