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| Name | Class |
|---|---|
| Massachusetts Institute of Technology | OTHER |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients scheduled for consult with gastroenterologist | |||
| Patients scheduled for diagnostic endoscopy |
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| Measure | Description | Time Frame |
|---|---|---|
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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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
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Massachusetts General Hospital | Boston | Massachusetts | 02114 | United States |
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| ID | Term |
|---|---|
| D005767 | Gastrointestinal Diseases |
| ID | Term |
|---|---|
| D004066 | Digestive System Diseases |
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