A team of researchers from the SABIEN group at the ITACA Institute of the Universitat Politècnica de València (UPV) has led an international study providing a comprehensive analysis of the use and impact of artificial intelligence (AI) in Neonatal Intensive Care Units (NICUs). Published in Seminars in Fetal and Neonatal Medicine, the study reviews a decade of research in this field and evaluates 41 studies applying AI in neonatal clinical settings.
Developed in collaboration with the Hospital Universitari i Politècnic La Fe, IIS La Fe, and Queen Mary University of London, the research analyses the evolution of these technologies, identifies technical, methodological, and ethical challenges, and defines priorities to support their safe clinical implementation.
A tool with a growing impact on neonatal care
The analysis shows that AI is playing a significant role in improving early diagnosis, advanced monitoring, and predicting complications in premature newborns and those with severe conditions. The most common applications focus on the cardiovascular, neurological, respiratory, and infectious systems, where algorithms can detect subtle clinical signals that may go unnoticed in conventional assessments.
“Among the most relevant advances are the early detection of sepsis, the estimation of brain maturation, the prediction of respiratory episodes, and the optimisation of continuous monitoring systems based on physiological signals, video, or sound”, explain ITACA researchers.
NICUs generate vast volumes of real-time data, and interpreting this information using AI can “improve clinical decision-making and anticipate complications, reducing risks and strengthening care for the most vulnerable newborns», highlights Vicente Traver, head of the SABIEN group and co-author of the article.
Outstanding challenges for safe clinical implementation
The study identifies several obstacles that continue to limit the widespread adoption of these technologies, including patient variability, poorly representative datasets, biases associated with non-invasive monitoring, and the lack of external validation in many of the reviewed studies.
It also underscores the need for user-friendly models for healthcare professionals, as well as larger, high-quality databases to improve the robustness and generalisability of AI algorithms.
Interdisciplinary collaboration and emerging ethical challenges
The research emphasises the importance of interdisciplinary collaboration among engineers, clinicians, data scientists, and ethics experts to drive technological progress in the neonatal–perinatal field.
“As computational models become more sophisticated and access to health data increases, the potential of AI to transform healthcare is considerable, ranging from predictive diagnosis to the development of personalised treatment plans», says Antonio Martínez Millana, Deputy Director of ITACA and a participant of the study.
However, significant challenges remain, including ensuring data privacy, rigorously validating models, and guaranteeing equitable access to emerging technologies. These issues are “key pillars of future research to build safe clinical environments and more accessible healthcare systems,” he adds.
Opportunities for more precise and personalised neonatology
Finally, the study identifies numerous opportunities to move towards more predictive and efficient NICUs. These include integrating multimodal data, developing real-time monitoring tools, and designing explainable, ethically responsible models. “These technologies represent a decisive opportunity to evolve towards more preventive, precise, and personalised care tailored to the needs of each newborn”, highlights Andrea García Montaner, a researcher at SABIEN.
The research was funded by the INBIO programme, which promotes innovation projects between the Hospital Universitari i Politècnic La Fe and the Universitat Politècnica de València, and supported by the RICORS-SAMID network and European NextGenerationEU funds, which foster advances in biomedical research and innovation applied to neonatal health.
REFERENCE: Antonio Martínez Millana, Álvaro Solaz-García, Andrea García Montaner, María Portolés Morales, Longwei Xiaod, Yan Sund, Vicente Traver, Máximo Vento, Pilar Sáenz-González; A systematic review on the use of artificial intelligence in the neonatal intensive care unit: far beyond the potential impact. Seminars in Fetal and Neonatal Medicine.
DOI: https://www.sfnmjournal.com/article/S1744-165X(25)00084-8/abstract