AI-driven laboratory workflows enable operation in the age of social distancing

Marescotti, Diego; Narayanamoorthy, Chandrasekaran; Bonjour, Filipe; Kuwae, Ken; Graber, Luc; Calvino-Martin, Florian; Ghosh, Samik; Hoeng, Julia

doi:10.1016/j.slast.2021.12.001

Cited by 11 publications

(2 citation statements)

References 20 publications

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“…Further developments and improvements that could be explored include integration with Laboratory Information Management Systems (LIMS) and full process automation through collaborative robots. Indeed, laboratories of the future are trending towards greater levels of integration, automation (Abolhasani and Kumacheva, 2023) and even the implementation of artificial intelligence (Marescotti et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Development and validation of automated methods for COVID-19 PCR MasterMix preparation

Fedele,

Hill,

Sweetford

et al. 2023

Preprint

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Polymerase Chain Reaction (PCR)-based assays were widely deployed during the SARS-CoV-2 pandemic for population-scale testing. High-throughput molecular diagnostic labora-tories required a high degree of process automation to cope with huge testing demand, fast turn-around times and quality requirements. However, the critical step of preparing a PCR MasterMix has often been neglected by process developers and optimisers, and is largely dependent upon operator skill for the manual pipetting of reagents to construct the PCR MasterMix. Dependence on manual procedures introduces variation, inconsistency, wastage and potentially risks data integrity. To address this issue, we developed a liquid-handler based solution for automated, traceable and compliant PCR MasterMix preparation. Here, we show that a fully automated PCR MasterMix protocol can substitute manual pipetting, without affecting clinical calling, accuracy or precision. Ultimately, this method reduced cost-per-test at a high-throughput laboratory by eliminating operator-induced wastage while improving the quality of results.

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Section: Discussionmentioning

confidence: 99%

Development and validation of automated methods for COVID-19 PCR MasterMix preparation

Fedele,

Hill,

Sweetford

et al. 2023

Preprint

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“…Their technological competence, data literacy, problemsolving skills, and adaptability are essential attributes of employability skills that are improved through this active participation. Technological Acceptance serves as a bridge, enabling AI-based DSS to more effectively affect the development of employable skills (Marescotti et al, 2022). It makes it easier for staff to use these tools, giving them access to data-driven insights and tailored advice that enhance their skill set.…”

Section: Discussionmentioning

confidence: 99%

AI and big data-driven decision support for fostering student innovation in music education at private underground colleges

Liu

2023

J INFORM SYSTEMS ENG

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This study investigates the transformative impact of AI-based Decision Support Systems (DSS) and Big Data Analytics (BDA) on student innovation and employability skills in an era of rapid technological advancement, with a focus on the mediating role of technological acceptance and the moderating role of resource availability. This study, which draws on a wide range of educational contexts and data sources, gives complete knowledge of the complex links between technology adoption, student results, and contextual factors. The results of this study show how AI-based DSS and BDA have a significant impact on musical education. These technological advancements enable tailored instruction and foster students' creative thinking. In order to prepare students for a work market that is rapidly changing, they act as a catalyst for improving employability skills. The study, however, emphasizes the complicated dynamics at work. Technological Acceptance emerges as a major mediating component, underlining the significance of students and instructors freely and effectively accepting technological tools. Furthermore, as a moderating factor, Resource Availability takes center stage, emphasizing the need for equitable access to educational resources to ensure that technology-driven advantages are accessible to all. The results of this study have broad repercussions. The adoption of AI and BDA by educational institutions is encouraged as transformative technologies for enhancing the learning process. Policymakers must create regulations that support equal access to technology and promote an innovative culture in the classroom. This study highlights for students how important it is to adopt new technologies, realizing how important they are in determining both their academic and career paths.

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