Minhua Chen

TL;DR: It is demonstrated that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals.

TL;DR: The required number of CS random measurements needed for successful reconstruction is derived based on easily-computed quantities, drawing on block-sparsity properties, and the resulting algorithm can be used for learning manifolds and for reconstructing signals from manifolds, based on compressive sensing projection measurements.

TL;DR: A gene signature for symptomatic influenza capable of detecting 94% of infected cases was generated and applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 infected and non-infected individuals with 92% accuracy.

TL;DR: Results show that RT-PCR–based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting.

TL;DR: The objective is to design a projection matrix to maximize key information-theoretic quantities with operational significance, including the mutual information between the signal and the projections or the Renyi entropy of the projections.