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Editorial
. 2022 Sep 5:10:1007799.
doi: 10.3389/fped.2022.1007799. eCollection 2022.

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

Affiliations
Editorial

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

Antoniya Georgieva et al. Front Pediatr. .
No abstract available

Keywords: big data and analytics; cardiotocography; decision support; electrocardiography; electroencephalography; electronic fetal monitoring; machine learning; pregnancy.

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Conflict of interest statement

Author MF holds patents on EEG and ECG processing, the founder of and consults for Digital Health companies commercializing the predictive potential of physiological time series for human health. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Key insights from the Research Topic and future directions. There is a growing awareness of the antecedents of intrapartum fetal reserve for the trial of labor which require an integration of the physiology of whole pregnancy and the well-known relationships between intrauterine adversity on one hand, and the perinatal and postnatal developmental trajectories on the other hand (Developmental Origins of Health and Disease, the DOHaD concept). Another key insight is the requirement for clinically actionable outcome labels in the prediction models that are being developed and the recognition of the fundamental constraints on the data sizes of the individually accessible cohorts. Therefore, there is a clear need for multinational and multidisciplinary work to address the different challenges and research questions, which are all integral to successfully improving the technologies for intrapartum fetal monitoring.

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

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