2019
DOI: 10.1039/c8lc01344f
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A smartphone fluorescence imaging-based mobile biosensing system integrated with a passive fluidic control cartridge for minimal user intervention and high accuracy

Abstract: A biosensor with minimal user interventions and high accuracy.

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Cited by 25 publications
(7 citation statements)
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“…The area under the curve (AUC) is 0.943, or 94.3%, which represents the accuracy of the platform (Zhou et al, 2011). Others have demonstrated comparable ROC curve analyses for smartphone platforms (Lee et al, 2019;Yeo et al, 2016). Combined, these results highlight the excellent sensitivity, specificity, and accuracy of the smartphone-based PD platform for measuring LAMP amplicons.…”
Section: Double-blinded Study In Pond Watermentioning
confidence: 93%
“…The area under the curve (AUC) is 0.943, or 94.3%, which represents the accuracy of the platform (Zhou et al, 2011). Others have demonstrated comparable ROC curve analyses for smartphone platforms (Lee et al, 2019;Yeo et al, 2016). Combined, these results highlight the excellent sensitivity, specificity, and accuracy of the smartphone-based PD platform for measuring LAMP amplicons.…”
Section: Double-blinded Study In Pond Watermentioning
confidence: 93%
“…Pharmaceuticals are used in livestock rearing, as prophylactics, therapeutics, or growth promoters (Landers et al, 2012). This results in the transfer of PPCPs and AMR through livestock defecation and addition of fecal waste to farmland, inevitably ending up in water bodies (Lee et al, 2019). Pharmaceuticals and personal care products are also used in aquaculture and are administered in feed or directly released into water.…”
Section: Natural Water Environmentsmentioning
confidence: 99%
“…Mobile phone has been used not only as a communication tool but also as a platform that can process information with the high-resolution camera and powerful computing capabilities. Different chemical and biological detection platforms based on smartphone have be proposed. Digital image colorimetry based on smartphone has been developed because of high efficiency, convenience and low-cost . All images can be decomposed into tricolor of red, yellow, and blue and represented by RGB (Red, Green, Blue) values.…”
Section: Introductionmentioning
confidence: 99%