Artificial intelligence applied to neonatal diagnosis and monitoring: a bibliographic review
DOI:
https://doi.org/10.63688/6xhtxj76Keywords:
artificial intelligence, neonatology, neonatal diagnosis, neonatal monitoring, machine learning, neonatal intensive care unitsAbstract
Introduction: Artificial intelligence (AI) has emerged as an innovative tool in healthcare due to its ability to analyze large volumes of data and support clinical decision-making. In neonatology, its application has gained increasing relevance because of its potential to improve early diagnosis, continuous monitoring, and the prediction of complications in newborns. Objective: To analyze the available scientific evidence on the application of artificial intelligence in neonatal diagnosis and monitoring, identifying its effectiveness, clinical impact, and main challenges. Method: A qualitative study with a documentary design was conducted through a literature review. The search was performed in the Scopus, Web of Science, and SciELO databases. After applying inclusion and exclusion criteria, 11 scientific studies were selected for analysis. Results: The findings showed that AI demonstrates high levels of accuracy in the detection of neonatal sepsis, retinopathy of prematurity, neonatal seizures, and neonatal mortality. In addition, it improved continuous clinical surveillance, early identification of adverse events, and risk stratification, promoting more timely and personalized clinical decisions. Conclusion: Artificial intelligence is a promising tool for optimizing neonatal diagnosis, monitoring, and care. Its implementation can contribute to improving clinical outcomes and reducing neonatal morbidity and mortality. However, challenges related to clinical validation, data quality, and ethical considerations still remain and require further research.
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Copyright (c) 2026 Patricia Graciela Nieto Gómez, Paola Estefania Salazar Altamirano, María José Herrera Manobanda, Sindy Marleyn García Paz (Autor/a)
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