Author

Maxime P. Cannesson

University of California, Los AngelesORCID 0000-0003-2120-1672Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Organism:human· 1 Research Focus:imputation· 1

Frequent Co-Authors

Brian L. HilliD· 2 shared Eran HalperiniD· 2 shared Ira S. HoferiD· 2 shared Nadav RakocziD· 2 shared Sriram SankararamaniD· 2 shared Aman MahajaniD· 1 shared Brandon JewiD· 1 shared Christine LeeiD· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Brian L. HillORCID

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2 papers

Recent·Most cited

Genetic & Genomic Medicinenpj Genomic MedicinePeer-reviewedAug 25, 2022

Methylation risk scores are associated with a collection of phenotypes within electronic health record systems

Mike Thompson, Brian L. Hill, Nadav Rakocz…·Eran Halperin

This study evaluates methylation risk scores (MRS) in clinical datasets, showing they improve EHR imputation and predict phenotypes better than polygenic risk scores or EHR-based methods alone.

59 citationstop 4%

humanelectronic health records

𝕏 PostBluesky

BioinformaticsBritish Journal of AnaesthesiaPeer-reviewedOct 15, 2019

Preoperative predictions of in-hospital mortality using electronic medical record data

Brian L. Hill, Robert J. Brown, Eilon Gabel…·Eran Halperin

This paper develops a machine learning model using EMR data to predict in-hospital mortality preoperatively, achieving higher accuracy than existing clinical scores.

103 citationstop 2%

electronic health recordsmachine learning (classical)

𝕏 PostBluesky