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.
Visa merStartår
2024
Slutår
2028
Beviljade finansiering
Finansiär
Finlands Akademi
Typ av finansiering
Akademiprojekt
Utlysning
Beslutfattare
Forskningsrådet för biovetenskap, hälsa och miljö
12.06.2024
12.06.2024
Övriga uppgifter
Finansieringsbeslutets nummer
361890
Vetenskapsområden
Biomedicinska vetenskaper
Forskningsområden
Biolääketieteet
Identifierade teman
public health, occupational health