Publications

AI-driven decision support systems and epistemic reliance: a qualitative study on obstetricians' and midwives' perspectives on integrating AI-driven CTG into clinical decision making.

Dlugatch R. et al, (2024), BMC medical ethics, 25

Prediction of Fetal Blood Pressure during Labour with Deep Learning Techniques

Tolladay J. et al, (2023), Bioengineering, 10, 775 - 775

Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care.

Dlugatch R. et al, (2023), BMC medical ethics, 24

Fetal heart rate responses in chronic hypoxaemia with superimposed repeated hypoxaemia consistent with early labour: a controlled study in fetal sheep

Lear CA. et al, (2023), BJOG: An International Journal of Obstetrics & Gynaecology

Predelivery placenta-associated biomarkers and computerized intrapartum fetal heart rate patterns

Bowe S. et al, (2023), AJOG Global Reports, 3, 100149 - 100149

Fetal Heart Rate Classification with Convolutional Neural Networks and the Effect of Gap Imputation on Their Performance

Asfaw D. et al, (2023), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13810 LNCS, 459 - 469

Editorial: Fetal-maternal monitoring in the age of artificial intelligence and computer-aided decision support: A multidisciplinary perspective

Georgieva A. et al, (2022), Frontiers in Pediatrics, 10

Cardiotocography and Clinical Risk Factors in Early Term Labor: A Retrospective Cohort Study Using Computerized Analysis With Oxford System

Lovers AAK. et al, (2022), Frontiers in Pediatrics, 10

Deceleration area and capacity during labour‐like umbilical cord occlusions identify evolving hypotension: a controlled study in fetal sheep

Georgieva A. et al, (2020), BJOG: An International Journal of Obstetrics & Gynaecology

Computer-based intrapartum fetal monitoring and beyond: A review of the 2nd Workshop on Signal Processing and Monitoring in Labor (October 2017, Oxford, UK).

Georgieva A. et al, (2019), Acta obstetricia et gynecologica Scandinavica

Multimodal Convolutional Neural Networks to Detect Fetal Compromise During Labor and Delivery

Petrozziello A. et al, (2019), IEEE Access, 7, 112026 - 112036

Understanding Fetal Heart Rate Patterns That May Predict Antenatal and Intrapartum Neural Injury

Lear CA. et al, (2018), Seminars in Pediatric Neurology, 28, 3 - 16

Doppler-based fetal heart rate analysis markers for the detection of early intrauterine growth restriction.

Stroux L. et al, (2017), Acta obstetricia et gynecologica Scandinavica, 96, 1322 - 1329

Computerized data-driven interpretation of the intrapartum cardiotocogram: a cohort study.

Georgieva A. et al, (2017), Acta obstetricia et gynecologica Scandinavica, 96, 883 - 891

Monitoring fetal maturation-objectives, techniques and indices of autonomic function.

Hoyer D. et al, (2017), Physiological measurement, 38, R61 - R88

Effect of signal acquisition method on the fetal heart rate analysis with phase rectified signal averaging.

van Scheepen JAM. et al, (2016), Physiological measurement, 37, 2245 - 2259

Authors' reply: Computerised interpretation of fetal heart rate patterns and correlation with fetal acidaemia.

Georgieva A. et al, (2014), BJOG : an international journal of obstetrics and gynaecology, 121, 1747 - 1748

Feature selection using genetic algorithms for fetal heart rate analysis.

Xu L. et al, (2014), Physiological measurement, 35, 1357 - 1371

Phase-rectified signal averaging for intrapartum electronic fetal heart rate monitoring is related to acidaemia at birth.

Georgieva A. et al, (2014), BJOG : an international journal of obstetrics and gynaecology, 121, 889 - 894

The effect of augmentation of labour with syntocinon on the fetal CTG using objective computerised analysis: a nested case-control study.

Aye CYL. et al, (2014), European journal of obstetrics, gynecology, and reproductive biology, 176, 112 - 118

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Publications