Selected article for: "artificial intelligence and highly sensitive testing"
Author: Hsiao, Wesley Wei-Wen; Le, Trong-Nghia; Pham, Dinh Minh; Ko, Hui-Hsin; Chang, Huan-Cheng; Lee, Cheng-Chung; Sharma, Neha; Lee, Cheng-Kang; Chiang, Wei-Hung
Title: Recent Advances in Novel Lateral Flow Technologies for Detection of COVID-19
  • Cord-id: 75bco7ah
  • Document date: 2021_8_25
    • ID: 75bco7ah
    Snippet: The development of reliable and robust diagnostic tests is one of the most efficient methods to limit the spread of coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, most laboratory diagnostics for COVID-19, such as enzyme-linked immunosorbent assay (ELISA) and reverse transcriptase-polymerase chain reaction (RT-PCR), are expensive, time-consuming, and require highly trained professional operators. On the other hand
    Document: The development of reliable and robust diagnostic tests is one of the most efficient methods to limit the spread of coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, most laboratory diagnostics for COVID-19, such as enzyme-linked immunosorbent assay (ELISA) and reverse transcriptase-polymerase chain reaction (RT-PCR), are expensive, time-consuming, and require highly trained professional operators. On the other hand, the lateral flow immunoassay (LFIA) is a simpler, cheaper device that can be operated by unskilled personnel easily. Unfortunately, the current technique has some limitations, mainly inaccuracy in detection. This review article aims to highlight recent advances in novel lateral flow technologies for detecting SARS-CoV-2 as well as innovative approaches to achieve highly sensitive and specific point-of-care testing. Lastly, we discuss future perspectives on how smartphones and Artificial Intelligence (AI) can be integrated to revolutionize disease detection as well as disease control and surveillance.

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