AI-Driven Biometric Analysis for Preterm Birth Risk Assessment
Background
Preterm births (babies born earlier than expected) and stillbirths (babies dying before birth) are significant social concerns. Although various factors such as maternal age, infections, and genetic abnormalities have been identified as potential causes, many remain unknown.
The risk of preterm births is also increasing due to changes in social factors, such as the trend toward advanced maternal age. In 2020, a WHO report highlighted the global burden of preterm births, describing it as a ‘silent emergency’ due to the lack of improvement in preterm birth rates over recent decades.
Preterm births and stillbirths are not just individual issues; their societal impact is profound. The extensive costs associated with tertiary care and subsequent life support are significant. In the USA, over $20 billion are spent annually on preterm birth management, while in the UK, nearly £2.5 billion are allocated, underscoring the substantial societal impact of preterm births.
Overview of the Research
This study aims to support medical professionals by analyzing biometric data to identify high-risk preterm birth patients in out-of-hospital settings, where medical resources are limited. By leveraging easily obtainable biometric information, the study uses AI to assess the risk of preterm birth.
The research will help to illuminate the “black box” of pregnancy outside hospital environments, potentially reducing unnecessary medical interventions and ensuring that medical resources are optimally allocated to those truly at high risk.
About the Research Results
We are currently preparing for a presentation at an academic conference and the publication of our first clinical research paper. The findings will also be shared on this page.
Inquiries
If participants in this study have any questions, please contact us using the form provided in the consent document.
Please note that due to privacy protection considerations, we are unable to respond to inquiries about this clinical research through the ‘Contact Us’ page on this website. We appreciate your understanding.
For further information, please refer to our privacy policy available at the following link.
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