This paper describes an application of Bayesian Networks to mo-del persons with multimorbidity using measurements of vital signs and lifestyle assessments. The model was developed as part of a project on the use of wearable and home sensors and tablet applications to help persons with multimorbidity and their carers manage their conditions in daily life. The training data was extracted from TILDA, an open dataset collected from a longitudinal health study of the older Irish population. A categorical BN structure was learnt using a score-based approach, with constraints on the ordering of variables. The prediction accuracy of the model is assessed using the Brier score in a cross-validation experiment. Finally, a user inter-face that allows to set some observed levels and query the resulting margi-nal probabilities from the BN is presented.
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