Browsing Publikasjoner fra CRIStin FHI by Subject "Machine learning"
Now showing items 1-5 of 5
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Aims and strategy for the implementation of machine learning in evidence synthesis in the Cluster for Reviews and Health Technology Assessments for 2021-2022
(Research report, 2021)Key messages: In 2020-2021, a team in the Cluster for Reviews and Health Technology Assessments, Division for Health Services at the Norwegian Institute of Public Health (NIPH) ran a project on machine learning (ML) related ... -
AMR-Diag: Neural network based genotype-to-phenotype prediction of resistance towards β-lactams in Escherichia coli and Klebsiella pneumoniae
(Peer reviewed; Journal article, 2021) -
Evaluering av OpenAlex
(Research report, 2023)For kunnskapsoppsummeringer er det et mål at litteratursøket identifiserer alle relevante studier. En ny søkekilde for å identifisere studier er OpenAlex, som er en videreføring av datasettet Microsoft Academic Graph (MAG). ... -
Implementering av maskinlæring i kunnskapsoppsummeringer i klynge for vurdering av tiltak: Sluttrapport 2021-2022
(Research report, 2023)Hovedbudskap Maskinlæring (ML) er et satsingsområde for klynge for vurdering av tiltak, Område for helsetjenester, FHI. Høsten 2021 overtok ML 2.0 arbeidet etter ML 1.0. Denne rapporten beskriver ML 2.0 teamet sitt arbeid, ... -
Using neural networks to support high-quality evidence mapping
(Peer reviewed; Journal article, 2021)Abstract Background: The Living Evidence Map Project at the Norwegian Institute of Public Health (NIPH) gives an updated overview of research results and publications. As part of NIPH’s mandate to inform evidence-based ...