A platform for phenotyping disease progression and associated longitudinal risk factors in large-scale EHRs, with application to incident diabetes complications in the UK Biobank.
Modern healthcare data reflect massive multi-level and multi-scale information collected over many years. The majority of the existing phenotyping algorithms use case-control definitions of disease. This paper aims to study the time to disease onset and progression and identify the time-varying risk factors that drive them.
Author(s): Kim, Do Hyun, Jensen, Aubrey, Jones, Kelly, Raghavan, Sridharan, Phillips, Lawrence S, Hung, Adriana, Sun, Yan V, Li, Gang, Reaven, Peter, Zhou, Hua, Zhou, Jin J
DOI: 10.1093/jamiaopen/ooad006