Author

Melissa Jay

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

Frequent Co-Authors

Christopher Barton· 2 shared Jacob S. CalvertiD· 2 shared Jana L. HoffmaniD· 2 shared Qingqing MaoiD· 2 shared Ritankar DasiD· 2 shared David W. ShimabukuroiD· 1 shared Grant Fletcher· 1 shared Lisa Y. ShiehiD· 1 shared

Activity by Year

2017-2018 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersBioinformatics

Christopher Barton

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2 papers

Recent·Most cited

Multicenter validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

Qingqing Mao, Melissa Jay, Jana L. Hoffman, Jacob S. Calvert, Christopher Barton, David W. Shimabukuro, Lisa Y. Shieh, Uli K. Chettipally, Grant Fletcher, Yaniv Kerem, Yifan Zhou, Ritankar Das

This paper validates a sepsis prediction algorithm using vital sign data across multiple settings, showing strong performance and generalizability.

BMJ Open · Jan 1, 2018Peer-reviewedBioinformatics

Pediatric Severe Sepsis Prediction Using Machine Learning

Thomas Desautels, Jana L. Hoffman, Christopher Barton, Qingqing Mao, Melissa Jay, Jacob S. Calvert, Ritankar Das

This study develops a machine learning algorithm using EHR data to predict pediatric severe sepsis onset, achieving high AUROC scores and outperforming existing clinical scores.

bioRxiv · Nov 22, 2017 · PreprintBioinformatics