التفاصيل البيبلوغرافية
| العنوان: |
Drug classification with a spectral barcode obtained with a smartphone Raman spectrometer. |
| المؤلفون: |
Kim, Un Jeong, Lee, Suyeon, Kim, Hyochul, Roh, Yeongeun, Han, Seungju, Kim, Hojung, Park, Yeonsang, Kim, Seokin, Chung, Myung Jin, Son, Hyungbin, Choo, Hyuck |
| المصدر: |
Nature Communications; 9/12/2023, Vol. 14 Issue 1, p1-9, 9p |
| مصطلحات موضوعية: |
CONVOLUTIONAL neural networks, IMAGE recognition (Computer vision), SMARTPHONES, SPECTROMETERS, IMAGING systems, RADIANT intensity, IMAGE sensors, CMOS image sensors |
| مستخلص: |
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. Smartphones are ubiquitous devices that have permeated into our daily life. Here, the authors demonstrate that a Smartphone Raman spectrometer can be used for drug classification by using a convolutional neural network to process its spectral barcode. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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