AIM4SafeBaby - version 1
Research type
Research Study
Full title
AIM4SafeBaby - Artificial Intelligence Monitoring for Safe birth of the baby.
IRAS ID
325198
Contact name
Rowan Connell
Contact email
Sponsor organisation
5GoreConn Ltd
Duration of Study in the UK
3 years, 6 months, 31 days
Research summary
AIM4SafeBaby project aims to create an innovative clinical decision support system that will convert pregnancy and labour data into knowledge-based guidelines for a safe baby-birth process. This tool will automatically monitor all the parameters, both maternal and foetal, to correlate and then display guidelines and predictions in a "traffic light" system for midwives, doctors and consultants so that they can predict the baby's distress with improved accuracy. This will minimise human error in assessing the baby's well-being to ensure safe delivery.
The key objectives of the projects are to:
1. Develop software and an application with API (Application Programming Interface) connectivity to existing maternity software, ultrasound, CTG (cardiotocography machines) to collect the anonymised patients' data.
2. Develop and train an AI (Artificial Intelligence) algorithm to predict foetal distress in real-time, based on the knowledge-based rules and inputs received from the CTG machine.
3. Develop relevant clinical guidelines.
4. Conduct safety trials in a relevant clinical environment.
5. Investigate any barriers/scope for improvisation.REC name
Wales REC 7
REC reference
23/WA/0229
Date of REC Opinion
4 Oct 2023
REC opinion
Further Information Favourable Opinion