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Network-medicine framework for studying disease trajectories in U.S. veterans

Ítalo Faria do Valle, Brian R. Ferolito, Hanna Gerlovin, Lauren Costa, Serkalem Demissie, Franciel Linares, Jérémy Cohen, David Gagnon, J. Michael Gaziano, Edmon Begoli, Kelly Cho, Albert-Ĺaszló Barabási

2022Scientific Reports12 citationsDOIOpen Access PDF

Abstract

A better understanding of the sequential and temporal aspects in which diseases occur in patient's lives is essential for developing improved intervention strategies that reduce burden and increase the quality of health services. Here we present a network-based framework to study disease relationships using Electronic Health Records from > 9 million patients in the United States Veterans Health Administration (VHA) system. We create the Temporal Disease Network, which maps the sequential aspects of disease co-occurrence among patients and demonstrate that network properties reflect clinical aspects of the respective diseases. We use the Temporal Disease Network to identify disease groups that reflect patterns of disease co-occurrence and the flow of patients among diagnoses. Finally, we define a strategy for the identification of trajectories that lead from one disease to another. The framework presented here has the potential to offer new insights for disease treatment and prevention in large health care systems.

Topics & Concepts

MEDLINEData scienceDiseaseComputer scienceMedicineBiologyPathologyBiochemistryChronic Disease Management StrategiesMachine Learning in HealthcareDiabetes Management and Education
Network-medicine framework for studying disease trajectories in U.S. veterans | Litcius