Advancements in Fetal Heart Rate Monitoring: A Report on Opportunities and Strategic Initiatives for Better Intrapartum Care.
Lovers A. et al, (2025), BJOG : an international journal of obstetrics and gynaecology
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
Gated Self Attention Convolutional Neural Networks for Predicting Adverse Birth Outcomes
Asfaw D. et al, (2024), Proceedings - 2024 16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024, 259 - 266
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