Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models.

ABSTRACT: The COVID-19 pandemic led to unparalleled pressure on healthcare services. Improved healthcare planning in relation to diseases affecting the respiratory system has consequently become a key concern. We investigated the value of integrating sales of non-prescription medications commonly bought for managing respiratory symptoms, to improve forecasting of weekly registered deaths from respiratory disease at local levels across England, by using over 2 billion transactions logged by a UK high street retailer from March 2016 to March 2020. We report the results from the novel AI (Artificial Intelligence) explainability variable importance tool Model Class Reliance implemented on the PADRUS model (Prediction of Amount of Deaths by Respiratory disease Using Sales). PADRUS is a machine learning m

SUBMITTER: Dolan E 

PROVIDER: S-EPMC10663456 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature