Latent variable mixture modelling and individual treatment prediction.

ABSTRACT: Understanding which groups of patients are more or less likely to benefit from specific treatments has important implications for healthcare. Many personalised medicine approaches in mental health employ variable-centred approaches to predicting treatment response, yet person-centred approaches that identify clinical profiles of patients can provide information on the likelihood of a range of important outcomes. In this paper, we discuss the use of latent variable mixture modelling and demonstrate its use in the application of a patient profiling algorithm using routinely collected patient data to predict outcomes from psychological treatments. This validation study analysed data from two services, which included n = 44,905 patients entering treatment. There were different patterns of reli

SUBMITTER: Saunders R 

PROVIDER: S-EPMC7417810 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature