Machine Learning-Based Quantification of (−)-<i>trans</i>-Δ-Tetrahydrocannabinol from Human Saliva Samples on a Smartphone-Based Paper Microfluidic Platform-Reference-Cited by-同舟云学术

Machine Learning-Based Quantification of (−)-trans-Δ-Tetrahydrocannabinol from Human Saliva Samples on a Smartphone-Based Paper Microfluidic Platform

Published:2022-08-15 Issue:34 Volume:7 Page:30064-30073
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Liang Yan¹,Zhou Avory²,Yoon Jeong-Yeol¹²^ORCID

Affiliation:

1. Department of Chemistry and Biochemistry, The University of Arizona, Tucson, Arizona 85721, United States

2. Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States

Funder

University of Arizona

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c03099

Reference39 articles.

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