12 May 2005 Biological agent detection and identification using pattern recognition
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Abstract
This paper discusses a novel approach for the automatic identification of biological agents. The essence of the approach is a combination of gene expression, microarray-based sensing, information fusion, machine learning and pattern recognition. Integration of these elements is a distinguishing aspect of the approach, leading to a number of significant advantages. Amongst them are the applicability to various agent types including bacteria, viruses, toxins, and other, ability to operate without the knowledge of a pathogen's genome sequence and without the need for bioagent-speciific materials or reagents, and a high level of extensibility. Furthermore, the approach allows detection of uncatalogued agents, including emerging pathogens. The approach offers a promising avenue for automatic identification of biological agents for applications such as medical diagnostics, bioforensics, and biodefense.
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Jerome J. Braun, Yan Glina, Nicholas Judson, Kevin D. Transue, "Biological agent detection and identification using pattern recognition", Proc. SPIE 5795, Chemical and Biological Sensing VI, (12 May 2005); doi: 10.1117/12.605913; https://doi.org/10.1117/12.605913
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