Author

Nicholas Saber

Dascena (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Assay:electronic health records· 1 Organism:human· 1

Frequent Co-Authors

Ritankar DasiD· 2 shared Andrea McCoy· 1 shared Anna Lynn-Palevsky· 1 shared Carol GuiD· 1 shared Christopher Barton· 1 shared Denise Gabel-Comeau· 1 shared Eduardo Pino· 1 shared Hamid Mohamadlou· 1 shared

Activity by Year

2018-2018 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Ritankar DasORCID

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2 papers

Recent·Most cited

Effect of a Sepsis Prediction Algorithm on Patient Mortality, Length of Stay, and Readmission

Hoyt Burdick, Eduardo Pino, Denise Gabel-Comeau, Andrea McCoy, Carol Gu, Jonathan Roberts, Joseph Slote, Nicholas Saber, Jana L. Hoffman, Ritankar Das

This paper evaluates a machine learning algorithm for predicting severe sepsis and shows it reduces mortality, length of stay, and readmission rates in real-world clinical use.

bioRxiv · Oct 31, 2018 · PreprintBioinformatics

Prediction of Acute Kidney Injury with a Machine Learning Algorithm using Electronic Health Record Data

Hamid Mohamadlou, Anna Lynn-Palevsky, Christopher Barton, Uli K. Chettipally, Lisa Y. Shieh, Jacob S. Calvert, Nicholas Saber, Ritankar Das

This study develops a machine learning model to predict acute kidney injury using electronic health records, achieving higher accuracy than traditional clinical scores.

Canadian Journal of Kidney Health and Disease · Jan 1, 2018Peer-reviewedBioinformatics