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Email

emerson.keenan@unimelb.edu.au

Credentials


Position
Honorary (Senior Fellow)
Department of Obstetrics, Gynaecology and Newborn Health
Education
PhD
University of Melbourne
Bachelors Degree (Honours)
University of Queensland
ORCID

0000-0003-1966-2293

Dr Emerson Keenan

Honorary (Senior Fellow)
Department of Obstetrics, Gynaecology and Newborn Health

43 Scholarly works
1 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Fusing Tabular Features and Deep Learning for Fetal Heart Rate Analysis: A Clinically Interpretable Model for Fetal Compromise Detection
    DOI: 10.1109/TBME.2026.3652309
  • 2025

    Journal article

    Impact of missing electronic fetal monitoring signals on perinatal asphyxia: a multicohort analysis
    DOI: 10.1038/s41746-025-01665-4
  • 2025

    Journal article

    Consumer insights from a feasibility study on remote and extended use of a novel non-invasive wearable fetal electrocardiogram monitor
    DOI: 10.1038/s41746-025-01628-9
  • 2025

    Journal article

    The association between circulating SIGLEC6 and preeclampsia: observational studies of seven cohorts
    DOI: 10.1016/j.ebiom.2025.105870
  • 2025

    Journal article

    The Fetal Region-specific Optimized Growth Standard (FROGS)—A fetal and birthweight centile calculator validated in a national population
    DOI: 10.1371/journal.pmed.1004634
  • 2025

    Journal article

    Deep learning to predict fetal acidemia
    DOI: 10.1016/j.ajog.2024.07.031
  • 2024

    Research grants (other domestic)

    Development of an Obstetric Growth Centile Calculator and App
Emerson Keenan

RECENT SCHOLARLY WORKS

  • 2025

    Journal article

    Quantifying Phase Coupling between Fetal Heart Rate and Uterine Contractions
    DOI: 10.1109/EMBC58623.2025.11253448
  • 2025

    Journal article

    Investigating the role of maternal heart rate variability in the onset of labor
    DOI: 10.3389/fmed.2025.1659620
  • 2025

    Journal article

    Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification
    DOI: 10.1109/JTEHM.2025.3548401
  • 2024

    Journal article

    Rapid detection of fetal compromise using input length invariant deep learning on fetal heart rate signals
    DOI: 10.1038/s41598-024-63108-6

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