Analysis of maternal biosignals using deep learning
Background
Preterm birth (when a baby is born earlier than expected) and stillbirth (when a baby dies before being born) are highly complex conditions that are still far from fully understood. Maternal age, sexually transmitted infections and fetal genetic abnormalities have all been identified as contributing factors, yet a large proportion of cases remain unexplained.
Today, against a backdrop of social change such as the rising age of pregnancy, there is growing concern that preterm birth is increasing. Progress in reducing stillbirth has likewise stagnated worldwide, making it a serious social issue.
Research Overview
In this study, we link biological signals acquired from the mother with clinical information on both the mother and the fetus during pregnancy, and use deep learning to analyze the relationships between them.
This allows us to obtain far more detailed insight into the condition of the fetus during pregnancy, which has long remained a black box.
About the study results
Findings from this study will be presented at academic conferences and published in peer-reviewed journals, and will also be disclosed on this page.
Contact
If you are a participant in this study and have any questions, please contact us using the form indicated in the informed consent form you received.
Please note that, in order to protect personal information, we are unable to respond to inquiries regarding this clinical study that are submitted through the general “Contact” page of this website. We appreciate your understanding.
References
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