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Email

loretta.gasparini@unimelb.edu.au

Credentials


Position
Associate Research Fellow - Research Focussed
Department of Audiology and Speech Pathology
Education
Doctoral Degree (Research) / PhD
University of Melbourne
ORCID

0000-0002-1561-5572

Dr Loretta Gasparini

Associate Research Fellow - Research Focussed
Department of Audiology and Speech Pathology

11 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Automated parts–of–speech tagging in 52 language varieties: Benchmarking towards establishing suitability for multilingual clinical language analysis
    DOI: 10.1016/j.nlp.2026.100226
  • 2026

    Journal article

    Measuring Environmental Noise for Babies in Special Care Nurseries and Neonatal Intensive Care Units on a Large Scale: Research Methods
    DOI: 10.1002/hsr2.71890
  • 2025

    Journal article

    Combining genetic and behavioral predictors of 11-year language outcome
    DOI: 10.1016/j.psychres.2025.116826
  • 2025

    Journal article

    A survey of large language model use in a hospital, research, and teaching campus
    DOI: 10.1017/dap.2025.10044
  • 2025

    Journal article

    A rapid review of the benefits and challenges of dynamic consent
    DOI: 10.1177/17470161241278064
  • 2025

    Journal article

    How to create accessible research summaries for the developmental language disorder community
    DOI: 10.1111/1460-6984.13142
  • 2024

    Journal article

    Identifying early language predictors: A replication of Gasparini et al. (2023) confirming applicability in a general population cohort
    DOI: 10.1111/1460-6984.13086
Loretta Gasparini

RECENT SCHOLARLY WORKS

  • 2023

    Journal article

    Using machine-learning methods to identify early-life predictors of 11-year language outcome
    DOI: 10.1111/jcpp.13733
  • 2022

    Journal article

    Synthesizing Core Outcome Sets for outcomes research in cohort studies: a systematic review
    DOI: 10.1038/s41390-021-01801-2
  • 2022

    Journal article

    Ten easy steps to conducting transparent, reproducible meta-analyses for infant researchers
    DOI: 10.1111/infa.12470

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