LATICE: Framework for Longitudinal Analysis of Time-Course Data from Patient Generated Health Data
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We aim to develop critical and enabling cyberinfrastructure for integrated analyses of longitudinal and time-series data from the multitude of sensors in common commercial wearables, in conjunction with the corresponding patient pharmacological and electronic health records EHRs). Effective analyses of this rich source of data has the potential to significantly enhance long-term individual well-being, reduce cost of healthcare, improve our understanding of pathology, associated sensor markers and prognoses, characterize the efficacy of drugs and identify adverse effects and interactions, and to enable a broad class of new data-driven studies. Architecting the proposed system poses significant challenges stemming from the heterogeneity of sensor devices and associated quality of data, diversity of populations and underlying pathologies, disparate drug regimes and responses, and complexity of the underlying analytics problems.