Using machine learning to improve diagnosis of functional seizures

Feasibility of machine learning to improve the diagnostic odyssey for functional seizures

NIH-funded research University of Pittsburgh at Pittsburgh · NIH-11054788

This study is working on a new tool to help doctors quickly figure out if someone has functional seizures instead of epilepsy, which can take a long time to diagnose, so that patients can get the right help sooner.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionUniversity of Pittsburgh at Pittsburgh NIH-funded
Lab location1 site (Pittsburgh, United States)
Project IDNIH-11054788 on NIH RePORTER

What this research studies

This research aims to enhance the diagnosis of functional seizures, which are often misidentified as epilepsy, by developing a computer-aided diagnostic tool. The project focuses on creating a Functional Seizures Likelihood Score (FSLS) that helps non-expert clinicians identify patients who may have functional seizures more quickly. By utilizing data from video-EEG monitoring, the research seeks to reduce the average delay of 8.4 years in diagnosing these seizures, ultimately improving patient outcomes. The study will also gather preliminary data for a future clinical trial that aims to streamline the diagnostic process using electronic health records.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals experiencing recurrent unprovoked seizures that have not been diagnosed as epilepsy.

Not a fit: Patients who have already been diagnosed with epilepsy or other seizure disorders may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could significantly reduce the time to accurately diagnose functional seizures, leading to better treatment outcomes and improved quality of life for patients.

How similar studies have performed: Other research has shown promise in using computer-aided diagnostic tools for improving diagnosis in various medical fields, suggesting potential success for this novel approach.

Where this research is happening

Pittsburgh, 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.
Last reviewed 2026-06-13 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.