NLP to Aid in the Evaluation and Diagnosis of FGIDs

NCT05501028 | Enrolling By Invitation

• 1 other identifier: 2018P001542
• Study Type: observational
• Target: 700
• Locations: 1 country
• Sites: 1

Brief Summary

The study has two arms, where the same natural language processing (NLP) and probabilistic graphical modeling technology will be utilized on patients' report of symptoms in both arms. The clinical arm is focused on patients presenting for consultation with a gastroenterologist. The endoscopy arm is focused generally on patients presenting for a diagnostic endoscopy, with the goal of capturing Functional Gastrointestinal Disorder (FGID) patients prior to diagnosis.

Conditions

Functional Gastrointestinal Disorders

Outcome Measures

Primary Outcomes (1)

• Latent themes present in patient descriptions of FGIDs symptoms

  Latent themes present in patient descriptions of FGIDs symptoms as generated by machine learning as well as quantitative comparisons to traditional metrics of patient descriptions including Rome IV criteria and patient descriptions of severity.

  08/09/2018-08/09/2023

Study Arms (2)

Patients scheduled for consult with gastroenterologist

Patients scheduled for diagnostic endoscopy

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Group 1: Patients who are scheduled for a consult in the MGH Gastroenterology Unit Group 2: Patients who are scheduled for a diagnostic endoscopy in the MGH Gastroenterology Unit

You may qualify if:

• Scheduled for consult in the Motility Clinic in the MGH Gastroenterology Unit or for diagnostic endoscopy in the MGH Gastroenterology Unit
• Patient must agree to have their interactions audio-recorded
• Informed consent form signed by the subjects

You may not qualify if:

• Non-native English speaker
• Patients unable to communicate their own symptoms

Sponsors & Collaborators

• Massachusetts General Hospital: lead
• Massachusetts Institute of Technology: collaborator

Study Sites (1)

Massachusetts General Hospital

Boston, Massachusetts, 02114, United States

Location

MeSH Terms

Conditions

Gastrointestinal Diseases

Condition Hierarchy (Ancestors)

Digestive System Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: March 1, 2022
• First Posted: August 15, 2022
• Study Start: August 9, 2018
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: May 6, 2026

Record last verified: 2025-11

Locations

US (1)