Laboratory Data and IBDQ—Effective Predictors for the Non-Invasive Machine-Learning-Based Prediction of Endoscopic Activity in Ulcerative Colitis

A suitable, non-invasive biomarker for assessing endoscopic disease activity (EDA) in ulcerative colitis (UC) has yet to be identified. Our study aimed to develop a cost-effective and non-invasive machine learning (ML) method that utilizes the cost-free Inflammatory Bowel Disease Questionnaire (IBDQ...

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Detalles Bibliográficos
Autores principales: Gavrilescu, Otilia, Popa, Iolanda Valentina, Dranga, Mihaela, Mihai, Ruxandra, Cijevschi Prelipcean, Cristina, Mihai, Cătălina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10253703/
https://www.ncbi.nlm.nih.gov/pubmed/37297804
http://dx.doi.org/10.3390/jcm12113609

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10253703/
https://www.ncbi.nlm.nih.gov/pubmed/37297804
http://dx.doi.org/10.3390/jcm12113609

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