Development of Digitally Obtainable 10-Year Risk Scores for Depression and Anxiety in the General Population.

ABSTRACT: The burden of depression and anxiety in the world is rising. Identification of individuals at increased risk of developing these conditions would help to target them for prevention and ultimately reduce the healthcare burden. We developed a 10-year predictive algorithm for depression and anxiety using the full cohort of over 400,000 UK Biobank (UKB) participants without pre-existing depression or anxiety using digitally obtainable information. From the initial 167 variables selected from UKB, processed into 429 features, iterative backward elimination using Cox proportional hazards model was performed to select predictors which account for the majority of its predictive capability. Baseline and reduced models were then trained for depression and anxiety using both Cox and DeepSurv, a deep

SUBMITTER: Morelli D 

PROVIDER: S-EPMC8414584 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature