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Drug classification with a spectral barcode obtained with a smartphone Raman spectrometer. | LitMetric

AI Article Synopsis

  • Researchers have developed a smartphone-based Raman spectrometer to classify drugs by their chemical components, achieving a high accuracy of 99.0%.
  • This spectrometer utilizes the CMOS image sensor and band pass filters to create a 2D intensity map of Raman spectral data, referred to as a "spectral barcode."
  • The technology allows for differentiation of brand-name drugs and identification of major components in unknown substances, promising advancements in research and commercial applications through a combination of spectroscopy and image recognition techniques.

Article Abstract

Measuring, recording and analyzing spectral information of materials as its unique finger print using a ubiquitous smartphone has been desired by scientists and consumers. We demonstrated it as drug classification by chemical components with smartphone Raman spectrometer. The Raman spectrometer is based on the CMOS image sensor of the smartphone with a periodic array of band pass filters, capturing 2D Raman spectral intensity map, newly defined as spectral barcode in this work. Here we show 11 major components of drugs are classified with high accuracy, 99.0%, with the aid of convolutional neural network (CNN). The beneficial of spectral barcodes is that even brand name of drug is distinguishable and major component of unknown drugs can be identified. Combining spectral barcode with information obtained by red, green and blue (RGB) imaging system or applying image recognition techniques, this inherent property based labeling system will facilitate fundamental research and business opportunities.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10465478PMC
http://dx.doi.org/10.1038/s41467-023-40925-3DOI Listing

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