Author

Martin Aasbrenn

University of CopenhagenORCID 0000-0003-3637-5763Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Research Focus:GWAS / association mapping· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Henrik HjalgrimiD· 1 shared Klaus RostgaardiD· 1 shared Mads MelbyeiD· 1 shared Piotr DworzyńskiiD· 1 shared Thomas Alexander GerdsiD· 1 shared Tune H. PersiD· 1 shared

Activity by Year

2020-2020 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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1 shared paperBioinformatics

Henrik HjalgrimORCID

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1 paper

Recent·Most cited

BioinformaticsScientific ReportsPeer-reviewedFeb 4, 2020

Nationwide prediction of type 2 diabetes comorbidities

Piotr Dworzyński, Martin Aasbrenn, Klaus Rostgaard…·Tune H. Pers

This study uses machine learning on Danish health registers to predict five-year risk of T2D comorbidities, showing modest improvements over reference models.

58 citationstop 2%

humanelectronic health records

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