A Study Using Artificial Intelligence to Identify Adults With Complex Perianal Fistulas Associated With Crohn's Disease (INTUITION-CPF)

Takeda

Status: Completed

Conditions: Rectal Fistula; Crohn Disease

Study type: Observational

Funder types: Industry

Identifiers

NCT04844593

Darvadstrocel-5001

Details and patient eligibility

About

Natural Language Processing and machine learning are examples of artificial intelligence tools. This study will check if these tools correctly identify people with Crohn's disease with complex perianal fistulas from their medical records.

Full description

This is a non-interventional, retrospective study of participants with CD and CPF in a clinical practice setting.

The study will enroll approximately 100 participants.

The study will have a retrospective data collection to select and analyze information from EMRs processed by an AI based analytics framework that uses machine learning and NLP methodologies.

All participants will be enrolled in one observational group.

• Participants with CD

This multi-center trial will be conducted in Spain. The overall duration of the study is approximately 36 months.

Enrollment: 32 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. CD participant diagnosed or not with CPF between January 1st 2015 and December 31st 2021.

Exclusion criteria

Not applicable.

Trial design

32 participants in 1 patient group

Participants With CD

Description:

Participants with CD diagnosed with or without CPF will be identified from EMRs through medical language application program interface (API) software. The AI will apply NLP and machine learning to identify and analyse text information in EMRs and thereby, extract medical information. The data will be collected retrospectively from January 1st 2015 and December 31st 2021.