The Role of Genetic Factors in Characterizing Extra-Intestinal Manifestations in Crohn’s Disease Patients: Are Bayesian Machine Learning Methods Improving Outcome Predictions?

The Role of Genetic Factors in Characterizing Extra-Intestinal Manifestations in Crohn’s Disease Patients: Are Bayesian Machine Learning Methods Improving Outcome Predictions?

(1) Background: The high heterogeneity of inflammatory bowel disease (IBD) makes the study of this condition challenging. In subjects affected by Crohn’s disease (CD), extra-intestinal manifestations (EIMs) have a remarkable potential impact on health status. Increasing numbers of patient...

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Bibliographic Details
Main Authors: Daniele Bottigliengo, Paola Berchialla, Corrado Lanera, Danila Azzolina, Giulia Lorenzoni, Matteo Martinato, Daniela Giachino, Ileana Baldi, Dario Gregori
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Journal of Clinical Medicine
Subjects:
Crohn’s disease
extra-intestinal manifestation
risk prediction
Bayesian methods
machine learning techniques
Online Access:https://www.mdpi.com/2077-0383/8/6/865

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https://www.mdpi.com/2077-0383/8/6/865

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