Detection of SARS-CoV-2 based on artificial intelligence-assisted smartphone: A review

Li, Yunxin; Zhang, Jinghui; Chen, Jisen; Zhu, Feng; Liu, Zhiqiang; Bao, Peng; Shen, Wei; Tang, Sheng

doi:10.1016/j.cclet.2023.109220

Cited by 2 publications

(1 citation statement)

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“…Thus, SDIC's versatility and educational applications could be expanded with digital videoing, where recording all phases of a colorimetric reaction will allow for holistic kinetic measurement and estimating reaction rates, constants, and other kinetic parameters. Additionally, SDIC's future will most likely include the use of machine learning and artificial intelligence for faster and more accurate colorimetric measurement or data analysis [76], thereby opening up new opportunities for a variety of educational applications and optimizations of the technique or specialized software that may reach even resource-constraint regions that would typically not reap the dividend of technological advancement.…”

Section: Future Perspectivesmentioning

confidence: 99%

Smartphone Digital Image Colorimetry: An Affordable Easy-To-Use Approach for Hands-On Training in Resource-Limited Settings

Markus,

Paul,

Marks

et al. 2024

Preprint

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Analytical instruments used for scientific research and education are often expensive. This limitation poses a challenge for schools and educators in low-income countries to provide practical science training to students. To address this problem, the improvisation of analytical instruments and instructional materials has emerged as a viable solution. By incorporating practical experiments into science education, students have the opportunity to engage directly with scientific instruments, conduct investigations, and collect data. This hands-on approach fosters a deeper understanding of scientific principles, enhances critical thinking skills, and cultivates scientific mindsets among students. Herein, we review and discuss, step-by-step, the approach of using a smartphone for quantitative analysis, referred to as smartphone digital image colorimetry (SDIC). SDIC, with its practicality and accessibility, utilizes smartphone digital cameras for image acquisition and the freely available image processing programs, such as ImageJ and smartphone Apps, for image quantification. Using SDIC can enable students in low-income countries to develop essential scientific skills, including critical thinking, data interpretation, and an evidence-based approach to scientific research. By leveraging the ubiquity and affordability of smartphone technology, SDIC offers an accessible and cost-effective approach to practical science education, bridging the gap between theory and practice in resource-constrained settings.

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Section: Future Perspectivesmentioning

confidence: 99%