NLP to Aid in the Evaluation and Diagnosis of FGIDs

Using Natural Language Processing of Novel Biopsychosocial Disease Constructs to Aid in the Evaluation and Diagnosis of Functional Gastrointestinal Disorders

Status

Enrolling by invitation

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05501028

Enrollment

700

Registered

2022-08-15

Start date

2018-08-09

Completion date

2026-12-01

Last updated

2026-05-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Functional Gastrointestinal Disorders

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Inclusion criteria

* 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

Exclusion criteria

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

Design outcomes

Primary

Measure	Time frame	Description
Latent themes present in patient descriptions of FGIDs symptoms	08/09/2018-08/09/2023	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.

Countries

United States

Outcome results