Improving specificity in Loop Mediated Amplification (LAMP) Diagnostic using Machine Learning

Ali Roula; Jeroen Nieuwland; Emma Hayhurst

Improving specificity in Loop Mediated Amplification (LAMP) Diagnostic using Machine Learning

Ali Roula, Jeroen Nieuwland, Emma Hayhurst

Research output: Contribution to conference › Paper › peer-review

Abstract

This abstract presents a novel approach to improving the specificity in RT-LAMP reaction outcomes. LAMP costs can be significantly lower than PCR. However, it does suffer from a higher false positive rate. Achieving comparable specificity and sensitivity would contribute a step closer toward the democratization of molecular diagnostics for wide range of viral and bacterial pathogens. In this preliminary study, we show that by using an algorithmic approach it is possible to significantly improve specificity when compared to the conventional presence/absence of reaction based method.

Original language	English
Number of pages	1
Publication status	Accepted/In press - 3 May 2022
Event	IEEE Engineering in Medicine and Biology Society: 44th Annual International Conference - UK, Glasgow Duration: 11 Jul 2022 → 15 Jul 2022 Conference number: 44 https://embc.embs.org/2022/

Conference

Conference	IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC 2022
City	Glasgow
Period	11/07/22 → 15/07/22
Internet address	https://embc.embs.org/2022/

Cite this

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title = "Improving specificity in Loop Mediated Amplification (LAMP) Diagnostic using Machine Learning",

abstract = "This abstract presents a novel approach to improving the specificity in RT-LAMP reaction outcomes. LAMP costs can be significantly lower than PCR. However, it does suffer from a higher false positive rate. Achieving comparable specificity and sensitivity would contribute a step closer toward the democratization of molecular diagnostics for wide range of viral and bacterial pathogens. In this preliminary study, we show that by using an algorithmic approach it is possible to significantly improve specificity when compared to the conventional presence/absence of reaction based method.",

author = "Ali Roula and Jeroen Nieuwland and Emma Hayhurst",

year = "2022",

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TY - CONF

T1 - Improving specificity in Loop Mediated Amplification (LAMP) Diagnostic using Machine Learning

AU - Roula, Ali

AU - Nieuwland, Jeroen

AU - Hayhurst, Emma

N1 - Conference code: 44

PY - 2022/5/3

Y1 - 2022/5/3

N2 - This abstract presents a novel approach to improving the specificity in RT-LAMP reaction outcomes. LAMP costs can be significantly lower than PCR. However, it does suffer from a higher false positive rate. Achieving comparable specificity and sensitivity would contribute a step closer toward the democratization of molecular diagnostics for wide range of viral and bacterial pathogens. In this preliminary study, we show that by using an algorithmic approach it is possible to significantly improve specificity when compared to the conventional presence/absence of reaction based method.

AB - This abstract presents a novel approach to improving the specificity in RT-LAMP reaction outcomes. LAMP costs can be significantly lower than PCR. However, it does suffer from a higher false positive rate. Achieving comparable specificity and sensitivity would contribute a step closer toward the democratization of molecular diagnostics for wide range of viral and bacterial pathogens. In this preliminary study, we show that by using an algorithmic approach it is possible to significantly improve specificity when compared to the conventional presence/absence of reaction based method.

M3 - Paper

T2 - IEEE Engineering in Medicine and Biology Society

Y2 - 11 July 2022 through 15 July 2022

ER -

Improving specificity in Loop Mediated Amplification (LAMP) Diagnostic using Machine Learning

Abstract

Conference

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