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 Med Ethics, 25

Multimodal Deep Learning for Predicting Adverse Birth Outcomes Based on Early Labour Data

Asfaw D. et al, (2023)

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

The association between placenta-associated circulating biomarkers and composite adverse delivery outcome of a likely placental cause in healthy post-date pregnancies.

Bowe S. et al, (2021), Acta Obstet Gynecol Scand, 100, 1893 - 1901

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

Georgieva A. et al, (2021), BJOG: An International Journal of Obstetrics & Gynaecology, 128, 1433 - 1442

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, 98, 1207 - 1217

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

Deep Learning for Continuous Electronic Fetal Monitoring in Labor

Petrozziello A. et al, (2018)

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

Advances in computing are driving progress in fetal monitoring.

Georgieva A., (2016), BJOG, 123

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Publications