Use of Natural Language Processing (NLP) and Machine Learning (ML) for the Identification of Patients With Crohn's Disease (CD) and Complex Perianal Fistulas (CPF) and Their Characterization in Terms of Clinical and Demographic Characteristics. A Multicentre, Retrospective, NLP Based Study
Use of Natural Language Processing (NLP) and Machine Learning (ML) for the Identification of Patients With Crohn's Disease (CD) and Complex Perianal Fistulas (CPF) and Their Characterization in Terms of Clinical and Demographic Characteristics. A Multicentre, Retrospective, NLP Based Study
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.
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.
Inclusion Criteria:
1. CD participant diagnosed or not with CPF between January 1st 2015 and December 31st 2021.
Exclusion Criteria:
Not applicable.