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Physical Sciences and EngineeringRR\C19
Published on Nov 22, 2020DOI

Reviews of "Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning"

Reviewers: Samuel Lalmuanawma (Mizoram University) | 📘📘📘📘📘 • Spyridon Kintzios (Agricultural University of Athens) | 📗📗📗📗◻️

by Samuel Lalmuanawma and Spyridon Kintzios
Published onNov 22, 2020
Reviews of "Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning"
key-enterThis Pub is a Review of
Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning
by Xu, Yang, Rather, Adil, Song, Shuang, Fang, Jen-Chun, Dupont, Robert L., Kara, Ufuoma I., Chang, Yun, Paulson, Joel A., Qin, Rongjun, Bao, Xiaoping, and Wang, Xiaoguang
  • papers.ssrn.com
Description

Rapid, robust virus detection techniques with ultrahigh sensitivity and selectivity are required for the outbreak of the pandemic coronavirus disease 2019 (COVI

To read the original manuscript, click the link above.

Summary of Reviews: This pre-print offers a novel diagnostic platform leveraging iquid crystal-based sensors and a smartphone app to improve PoC reliability. Reviewers found the included claims reliable, but emphasize the work represents a proof-of-concept.

Reviewer 1 (Samuel Lalmuanawma) | 📘📘📘📘📘

Reviewer 2 (Spyridon Kintzios) | 📗📗📗📗◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

To read the reviews, click the links below. 

Connections
1 of 2
A Supplement to this Pub
Review 2: "Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning"
Review 2: "Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning"
by Spyridon Kintzios
  • Published on Nov 22, 2020
  • rrid.mitpress.mit.edu
Description

This pre-print offers a novel diagnostic platform leveraging iquid crystal-based sensors and a smartphone app to improve PoC reliability. Reviewers found the included claims reliable, but emphasize the work represents a proof-of-concept.

A Supplement to this Pub
Review 1: "Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning"
Review 1: "Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning"
by Samuel Lalmuanawma
  • Published on Nov 22, 2020
  • rrid.mitpress.mit.edu
Description

This pre-print offers a novel diagnostic platform leveraging iquid crystal-based sensors and a smartphone app to improve PoC reliability. Reviewers found the included claims reliable, but emphasize the work represents a proof-of-concept.

License
Creative Commons Attribution 4.0 International License (CC-BY 4.0)
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Rapid Reviews Infectious Diseases
Rapid Reviews Infectious Diseases
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