NLP to Aid in the Evaluation and Diagnosis of FGIDs

N/AEnrolling By InvitationNCT05501028

Massachusetts General Hospital700 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

700

Conditions

Functional Gastrointestinal Disorders

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

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

Locations (1)

Massachusetts General Hospital

Boston, Massachusetts, United States

Outcomes

Primary Outcomes

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.

Time frame: 08/09/2018-08/09/2023

Data from ClinicalTrials.gov

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