Development and prospective validation of a deep learning model to detect abnormal clinical laboratory measurements in the entire Finnish population

Bidragets beskrivning

One hundred forty-two million clinical laboratory tests were performed in Finland in 2022, making it the highest-volume healthcare service. Current approaches to blood testing in primary healthcare are opportunistic and do not consider the richness of health data or integrate genetic information. Importantly, we showed that individuals from a disadvantaged socio-economic background get tested less, while other individuals are over-tested. We hypothesize that AI can be successfully employed to identify individuals who are likely to have abnormal values. We propose to develop and prospectively validate an AI approach to identify individuals who would benefit most from laboratory testing. We will do that using the extensive health and genetic data resources. Finally, we will recontact 2,000 individuals with predicted poor kidney function. This will allow us to understand the quality of our approach, while potentially identifying individuals with underdiagnosed chronic kidney disease.
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Startår

2024

Slutår

2028

Beviljade finansiering

Andrea Ganna Orcid -palvelun logo
599 886 €

Finansiär

Finlands Akademi

Typ av finansiering

Akademiprojekt

Beslutfattare

Forskningsrådet för biovetenskap, hälsa och miljö
12.06.2024

Övriga uppgifter

Finansieringsbeslutets nummer

361890

Vetenskapsområden

Biomedicinska vetenskaper

Forskningsområden

Biolääketieteet

Identifierade teman

public health, occupational health