Active — Not RecruitingNot Applicable

Using NLP and Neural Networks to Autonomously Identify Severe Asthma and Determine Study Eligibility in a Large Healthcare System

United States31,795 participantsStarted 2023-05-01

Plain-language summary

The study aims to to use new technologies (ML, AI, NLP), to autonomously identify moderate to severe asthma populations within an EHR system, describe differences in treatment patterns across different populations, and determine trial eligibility. Primary Objectives Please ensure you detail primary objectives Aim 1. Determine and validate a diagnosis of severe asthma (SA) using predictive features obtained from the Scripps Health EHR. * Aim 1a: Use ML applied to structured EHR data to predict SA. Use the opinion of 2 specialty-trained physicians and ATS guidelines to determine model accuracy. * Aim 1b: Use NLP applied to unstructured text to predict SA. Determine model accuracy as above in Aim 1a. * Aim 1c: Use a combination of ML applied to structured data to predict SA. Determine model accuracy as above in Aim 1a.

Who can participate

Age range6 Years – 85 Years

SexALL

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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: \- Demographics: Males \~ 40%, Blacks \~ 5-10%, Hispanic \~15-30%, Urban \~80-90% Exclusion Criteria: * None

What they're measuring

Identification of Patients with Severe Asthma

Timeframe: 4 years

Trial details

NCT IDNCT06389058

SponsorSan Diego State University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2026-12

View on ClinicalTrials.gov More Severe Asthma trials