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

Engineering Research and Innovation Group

Allbwn ymchwil: Cyfraniad at gynhadledd › Papur › adolygiad gan gymheiriaid

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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.

Iaith wreiddiol	Saesneg
Nifer y tudalennau	1
Statws	Wedi’i dderbyn/Yn y wasg - 3 Mai 2022
Digwyddiad	IEEE Engineering in Medicine and Biology Society: 44th Annual International Conference - UK, Glasgow Hyd: 11 Gorff 2022 → 15 Gorff 2022 Rhif y gynhadledd: 44 https://embc.embs.org/2022/

Cynhadledd

Cynhadledd	IEEE Engineering in Medicine and Biology Society
Teitl cryno	EMBC 2022
Dinas	Glasgow
Cyfnod	11/07/22 → 15/07/22
Cyfeiriad rhyngrwyd	https://embc.embs.org/2022/

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@conference{e0e7dc703498474ca478350266d54f44,

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",

month = may,

day = "3",

language = "English",

note = " IEEE Engineering in Medicine and Biology Society : 44th Annual International Conference, EMBC 2022 ; Conference date: 11-07-2022 Through 15-07-2022",

url = "https://embc.embs.org/2022/",

}

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

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