Phuong is a part-time DPhil student based at the Big Data Institute. She is investigating whether unsupervised and semi-supervised computational methods can be used on electronic health records to identify and understand temporal change-points, in particular whether they can help to distinguish between artefacts caused by e.g. changes in data collection methods versus real epidemiological trends.
She also currently works as a Medical Statistician in the Nuffield Department of Medicine which she joined in 2012. She has a BSc in Mathematics from Warwick University, an MSc in Applied Statistics from Oxford University, and worked for several years as a software developer before joining academia.
Health Record Hiccups - 5526 real-world time series with change points labelled by crowd-sourced visual inspection
QUAN TP. et al, (2023), GigaScience
Penicillin Binding Protein Substitutions Co-occur with Fluoroquinolone Resistance in ‘Epidemic’ Lineages of Multi Drug-Resistant Clostridioides difficile
DINGLE K. et al, (2023), mBio
daiquiri: Data Quality Reporting for Temporal
Quan TP., (2022), Journal of Open Source Software, 7, 5034 - 5034
A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.
COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium. Electronic address: firstname.lastname@example.org None. and COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium None., (2022), Cell, 185, 916 - 938.e58
Antimicrobial resistance in commensal opportunistic pathogens isolated from non-sterile sites can be an effective proxy for surveillance in bloodstream infections.
Vihta K-D. et al, (2021), Sci Rep, 11