Author:
Mendis Lochana,Palaniswami Marimuthu,Keenan Emerson,Brownfoot Fiona
Abstract
AbstractStandard clinical practice to assess fetal well-being during labour utilises monitoring of the fetal heart rate (FHR) using cardiotocography. However, visual evaluation of FHR signals can result in subjective interpretations leading to inter and intra-observer disagreement. Therefore, recent studies have proposed deep-learning-based methods to interpret FHR signals and detect fetal compromise. These methods have typically focused on evaluating fixed-length FHR segments at the conclusion of labour, leaving little time for clinicians to intervene. In this study, we propose a novel FHR evaluation method using an input length invariant deep learning model (FHR-LINet) to progressively evaluate FHR as labour progresses and achieve rapid detection of fetal compromise. Using our FHR-LINet model, we obtained approximately 25% reduction in the time taken to detect fetal compromise compared to the state-of-the-art multimodal convolutional neural network while achieving 27.5%, 45.0%, 56.5% and 65.0% mean true positive rate at 5%, 10%, 15% and 20% false positive rate respectively. A diagnostic system based on our approach could potentially enable earlier intervention for fetal compromise and improve clinical outcomes.
Funder
Melbourne Research Scholarship
Graeme Clark Institute for Biomedical Engineering at University of Melbourne
National Health and Medical Research Council
Publisher
Springer Science and Business Media LLC
Reference51 articles.
1. United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Never Forgotten: The situation of stillbirth around the globe. Report, United Nations Children’s Fund, New York (2023).
2. Vogel, J. et al. Maternal complications and perinatal mortality: Findings of the World Health Organization Multicountry survey on maternal and newborn health. BJOG Int. J. Obstet. Gynaecol. 121, 76–88 (2014).
3. Bhutta, Z. A. et al. Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost?. The Lancet 384, 347–370 (2014).
4. Goldenberg, R. L., Harrison, M. S. & McClure, E. M. Stillbirths: The hidden birth asphyxia—US and global perspectives. Clin. Perinatol. 43, 439–453 (2016).
5. Ayres-de Campos, D., Arulkumaran, S. & FIGO Intrapartum Fetal Monitoring Expert Consensus Panel. FIGO consensus guidelines on intrapartum fetal monitoring: Physiology of fetal oxygenation and the main goals of intrapartum fetal monitoring. Int. J. Gynecol. Obstet. 131, 5–8 (2015).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献