2022
DOI: 10.1021/acsomega.2c03099
|View full text |Cite
|
Sign up to set email alerts
|

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

Abstract: (−)- trans -Δ-Tetrahydrocannabinol (THC) is a major psychoactive component in cannabis. Despite the recent trends of THC legalization for medical or recreational use in some areas, many THC-driven impairments have been verified. Therefore, convenient, sensitive, quantitative detection of THC is highly needed to improve its regulation and legalization. We demonstrated a biosensor platform to detect and quantify THC with a paper microfluidic chip and a handheld smartphone-based fluorescenc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(2 citation statements)
references
References 39 publications
0
1
0
Order By: Relevance
“…They achieved an LOD of 0.17 ng/mL and the test was unaffected by consumption of coffee, alcohol, or tobacco. Following this principle, Liang et al developed a competitive immunoassay paper microfluidic chip with anti-THC-conjugated fluorescent NPs (Liang et al 2022 ).
Fig.
…”
Section: Thc Sensing Technologiesmentioning
confidence: 99%
“…They achieved an LOD of 0.17 ng/mL and the test was unaffected by consumption of coffee, alcohol, or tobacco. Following this principle, Liang et al developed a competitive immunoassay paper microfluidic chip with anti-THC-conjugated fluorescent NPs (Liang et al 2022 ).
Fig.
…”
Section: Thc Sensing Technologiesmentioning
confidence: 99%
“…It is wise to use machine learning algorithms to address these challenges. Liang et al demonstrated a machine-learning platform for detecting cannabis [128]. They use a microfluidic competitive immunoassay and a smartphone-based fluorescence microscope to extract results and analyze them further.…”
Section: Health Monitormentioning
confidence: 99%