+44 (0)1865 857854
I have developed my career in biomedical research, building on my expertise in machine learning, computing and mathematics, but specialising in intrapartum (in labour) fetal monitoring. I am now leading an ambitious programme to develop data-driven decision-support software in this clinical field. I am uniquely positioned to achieve this by working with the world’s largest and most complete birth cohort of routine labour data (100,000 deliveries).
I obtained a BSc(Hons) in Applied Mathematics from the Technical University of Sofia (Bulgaria) and a PhD in Computer Science from Portsmouth University. I joined the Nuffield Department of Obstetrics and Gynaecology and the Institute of Biomedical Engineering at Oxford for a post-doctoral position in 2007. In 2012, I founded the Oxford Centre for Fetal Monitoring Technologies, of which I am the Scientific Director. In 2016 I was awarded a NIHR Career Development Fellowship to grow my independent research group. In the same year, I also joined the newly formed Big Data Institute at Oxford.
BSc (Hons) PhD
Associate Professor & Scientific Director, Oxford Centre for Fetal Monitoring Technologies
- NIHR Career Development Fellow
- Wolfson College Research Fellow
- Group Leader
- Based jointly at the Big Data Institute and the Nuffield Department of Women's and Reproductive Health
Committed to preventing fetal compromise in labour
INTEREST TO JOIN?
We are looking for an Obstetric Research Fellow, from ST1 to even a consultant level - as long as their interest in fetal monitoring and the drive for clinical improvements are strong: https://www.wrh.ox.ac.uk/team/antoniya-georgieva/compose
And very soon we will be advertising for a Post-doctoral Scientist in Deep Learning and for a Research Midwife. Please get in touch if you may be interested.
I am leading a research team to develop a data-driven cardiotocography (CTG) system to continuously assess fetal wellbeing during term labour. CTG is the gold standard worldwide to detect if a fetus may benefit from an emergency delivery. Unreliable, empirical CTG interpretation will be replaced with quantified computer- and data-based individualised risk assessment.
We already have a prototype system (OxSys), as the starting point. It is derived from a large birth cohort (100,000 term deliveries) by systematic analysis of computer-based CTG features and clinical risk factors in relation to perinatal outcomes. In tests 'off-line' with the data, the current prototype has shown to perform better than clinicians in clinical practice. We have developed a tablet app that runs OxSys in real time data at the John Radcliffe Hospital, analysing all CTGs as they are being taken (maternity admission unit, delivery suite or Level 6). We are continuously improving the app's interface in collaboration with the clinicians. The app takes in information from the user about any risk factors if present and modifies the analysis accordingly.
In the coming years, we will continue to use 'big data' to derive new understanding and improved methods for CTG interpretation in the patient-specific clinical context. Beyond this, we will ensure refined optimal performance of OxSys on the birth cohort; validate OxSys on additional data from Oxford & London (approx. 40,000 births). We will then take the first steps towards translation to the bedside.
We are already working with partners across other hospitals in UK and EU to prepare for multicentre clinical tests, please get in touch if you may be interested.
Our work will potentially benefit families, clinicians and healthcare systems by reducing brain injuries, perinatal deaths and unnecessary interventions
SPECIAL ISSUE, CALL FOR PAPERS
Submission is now open for a Research Topic in Frontiers of Pediatrics, the final deadline is 31 Jan 2021:
National Institute for Health Research (NIHR)
Action Medical Research
Oxford University Innovation
For more information, including recent publications and up-coming international Workshop, please look at our group's website: Oxford Centre for Fetal Monitoring Technologies
We are an organiser of the international Workshop on Signal Processing and Monitoring (SPaM) in Labour, with its 3rd Workshop to be held 28-30 Oct 2019 in Porto, Portugal - see webpage.
Georgieva A. et al, (2019), Acta Obstetricia et Gynecologica Scandinavica, 98, 1207 - 1217
Petrozziello A. et al, (2019), IEEE Access, 7, 112026 - 112036
Lear CA. et al, (2018), Seminars in Pediatric Neurology, 28, 3 - 16
Deep Learning for Continuous Electronic Fetal Monitoring in Labor
Petrozziello A. et al, (2018)
Stroux L. et al, (2017), Acta Obstetricia et Gynecologica Scandinavica, 96, 1322 - 1329