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Drug classification with a spectral barcode obtained with a smartphone Raman spectrometer

Medicine and Health

Drug classification with a spectral barcode obtained with a smartphone Raman spectrometer

U. J. Kim, S. Lee, et al.

Discover how a revolutionary smartphone-based Raman spectrometer is transforming drug classification with an astonishing 99.0% accuracy! This groundbreaking research, conducted by Un Jeong Kim and colleagues, showcases a novel 'spectral barcode' method that even distinguishes between brands, merging cutting-edge technology with practical applications.... show more
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.
Publisher
Nature Communications
Published On
Aug 29, 2023
Authors
Un Jeong Kim, Suyeon Lee, Hyochul Kim, Yeongeun Roh, Seungju Han, Hojung Kim, Yeonsang Park, Seokin Kim, Myung Jin Chung, Hyungbin Son, Hyuck Choo
Tags
Raman spectrometer
drug classification
spectral barcode
convolutional neural network
brand identification
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