TY - JOUR
T1 - Analysis of urine using electronic tongue towards non-invasive cancer diagnosis
AU - Zniber, Mohammed
AU - Vahdatiyekta, Parastoo
AU - Huynh, Tan-Phat
N1 - Funding Information:
TPH would like to acknowledge the Academy of Finland (Grant No. 323240 ). PY thanks the financial support from the EDUFI Fellowship.
Publisher Copyright:
© 2022 The Authors
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.
AB - Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.
KW - Cancer diagnosis
KW - Electronic tongue
KW - Machine learning
KW - Urine
UR - http://www.scopus.com/inward/record.url?scp=85140224099&partnerID=8YFLogxK
U2 - 10.1016/j.bios.2022.114810
DO - 10.1016/j.bios.2022.114810
M3 - Review Article or Literature Review
AN - SCOPUS:85140224099
SN - 0956-5663
VL - 219
JO - Biosensors and Bioelectronics
JF - Biosensors and Bioelectronics
M1 - 114810
ER -