Project description
AI for foetal monitoring
Cardiotocography (CTG) helps clinicians monitor foetal well-being during labour. It tracks foetal heart rate and uterine contractions to detect problems like oxygen deprivation, which can lead to serious harm or death. Interpretation depends heavily on clinical experience, which makes decisions subjective and sometimes inconsistent. Supported by the Marie Skłodowska-Curie Actions programme, the BLOOM project is developing an AI system to support decision-making during labour. It combines CTG data with ultrasound growth patterns and maternal health records from electronic systems. It also uses a pathophysiological approach that accounts for individual foetal responses and maternal conditions. The system will be developed and validated to improve accuracy in assessing foetal well-being.
Objective
Cardiotocography (CTG) is a vital tool for monitoring fetal well-being during labor, recording fetal heart rate and uterine contractions to detect issues like hypoxia, which can cause neonatal deaths or long-term neurological damage. Early detection through CTG enables timely interventions, such as emergency cesarean sections, reducing risks. However, interpreting CTG data is challenging and depends heavily on clinician expertise, making assessments sometimes subjective and prone to error. This has driven interest in integrating artificial intelligence (AI) into CTG analysis to support clinicians with more accurate and timely decision-making. While AI shows promise in enhancing CTG interpretation, a significant challenge remains the absence of a universally accepted standard for assessing fetal outcomes. Many existing methods rely on surrogate markers or rigid scoring systems that fail to account for the complex physiological responses of individual fetuses. A pathophysiological approach, which considers unique fetal compensatory mechanisms and maternal health factors like hypertension or gestational diabetes, can provide a more nuanced and precise assessment of fetal well-being. The Birth and Labor Outcome Optimization through Multimodal AI (BLOOM) project is designed to address these challenges. It aims to develop, implement, and validate an advanced AI system specifically for use during labor. This system will integrate multimodal data, including fetal growth patterns from ultrasound screenings, maternal health conditions from electronic health records (EHR), and pathophysiological interpretations of CTG data. By combining these personalized factors with cutting-edge AI technologies, BLOOM seeks to create a more accurate and effective tool for assessing fetal well-being during labor, ultimately improving clinical outcomes and personalizing care.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- medical and health sciences clinical medicine obstetrics fetal medicine
- medical and health sciences clinical medicine embryology
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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66100 Chieti
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.