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Intelligent health system for investigation and consenting COVID-19 patients and precision medicine

Advancing frontiers of clinical research, we discuss the need of the intelligent health systems to support deeper investigation of COVID-19. We hypothesize that convergence of the healthcare data and staggering developments in artificial intelligence have potential to elevate recovery process with diagnostic and predictive analysis to identify major causes of mortality, modifiable risk factors and actionable information that supports early detection and prevention of COVID-19. However, current constraints include recruitment of COVID-19 patients for research; translational integration of electronic health records and diversified public datasets; and development of artificial intelligence systems for data-intensive computational modeling to assist clinical decision making. We propose a novel nexus of machine learning algorithms to examine COVID-19 data granularity from population studies to subgroups stratification and ensure best modeling strategies within the data continuum.