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Chronic Conditions

Overview of prediction pipeline and models used across prediction tasks. We specified 3 modelling tasks for predicting premature death among people with inflammatory bowel disease (IBD). We then used 3 types of models, namely logistic regression, random forest, and Extreme Gradient Boosting (XGBoost); XGBoost was the only model used for task 3 as it enabled direct modelling of missing data (those without conditions would have missing data). See Related Content for accessible version. Note: CCS = chronic coronary syndrome, CHF = congestive heart failure, COPD = chronic obstructive pulmonary disease, ED = emergency department, HTN = hypertension, MI = myocardial infarction, RA = rheumatoid arthritis.

AI Finds Nearly Half of IBD Patients Die Prematurely

Study highlights pervasiveness of inflammation in American diet

Study highlights pervasiveness of inflammation in American diet

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A shaking hand

Conditions like celiac disease, Parkinson’s could be detected 10 years earlier

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