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Contact


Email

vlada.rozova@unimelb.edu.au

Credentials


Position
Senior Research Fellow, Applied Machine Learning
Centre for Digital Transformation of Health
Education
PhD
Macquarie University
Masters (Research)
Moscow State University
ORCID

0000-0003-1032-4650

Dr Vlada Rozova

Senior Research Fellow, Applied Machine Learning
Centre for Digital Transformation of Health

18 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Evaluating the Fitness for Purpose of Primary Care Data from Electronic Health Records for Automated Antimicrobial Prescribing Audits
    DOI: 10.1055/a-2839-8787
  • 2026

    Conference Proceedings

    Why Do Self-Harm Prediction Models Struggle to Generalise? – Lexical and Semantic Variations in Emergency Department Triage Notes
    DOI: 10.18653/v1/2026.clpsych-1.31
  • 2025

    Journal article

    Bridging the Gap: Challenges and Strategies for the Implementation of Artificial Intelligence-based Clinical Decision Support Systems in Clinical Practice
    DOI: 10.1055/s-0044-1800729
  • 2025

    Journal article

    A systematic review on how primary care electronic medical record data have been used for antimicrobial stewardship
    DOI: 10.1017/ash.2024.499
  • 2025

    Conference Proceedings

    Automated Detection of Invasive Fungal Infections in Clinical Reports Using Medical Language Models
    DOI: 10.3233/SHTI250990
  • 2024

    Book Chapter

    Designing a Digital Health Solution: A Platform for Automated Surveillance of Fungal Infection
    DOI: 10.3233/SHTI231241
  • 2024

    Journal article

    Deep learning for early detection of papillary bladder cancer on a limited set of cystoscopic images
    DOI: 10.47093/2218-7332.2024.953.15
Vlada Rozova

RECENT SCHOLARLY WORKS

  • 2023

    Journal article

    Detecting evidence of invasive fungal infections in cytology and histopathology reports enriched with concept-level annotations
    DOI: 10.1016/j.jbi.2023.104293
  • 2023

    Conference Proceedings

    Natural Language Processing for Clinical Text
  • 2023

    Conference Proceedings

    CRF-based recognition of invasive fungal infection concepts in CHIFIR clinical reports

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