A systematic review on the use of artificial intelligence in the neonatal intensive care unit: far beyond the...

To explore the applicability of artificial intelligence (AI) in neonatal intensive care units (NICUs), identifying key trends in AI-driven technologies and their roles in the prognosis, classification, monitoring and forecasting of neonatal conditions.

A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-guided systematic review was conducted across MEDLINE, EMBASE, Cochrane, and IEEE Xplore, covering studies published between January 2013 and December 2023. A total of 318 studies were initially retrieved. After removing 61 duplicates and screening 257 articles by eligibility criteria, 64 studies were assessed for full-text eligibility, leading to the final inclusion of 41 studies.

The predominant AI application referred to conditions in the following systems: cardiovascular (n = 9, 21.9 %), neural/brain (n = 8, 19.5 %), respiratory (n = 8, 19.5 %), immune (infections) (n = 6, 14.6 %), gastrointestinal (n = 2, 4.9 %), and microvascular diseases (n = 1, 2.4 %). Additionally, six studies focused on monitoring systems or body positioning (categorized as "Not Disease"), and one study (2.4 %) addressed mortality prediction. Regarding the purposes of AI application, prognosis (n = 23, 56.1 %) was the most common, followed by classification (n = 14, 34.1 %), monitoring (n = 5, 12.2 %), and symptom forecasting (n = 1, 2.4 %). More than 70 % of studies (n = 29, 70.7 %) lacked a validation procedure, highlighting a critical gap in methodological rigor.

Our findings underscore the potential benefits of the use of AI in neonatology, possibly resulting in improved patient outcomes and enhanced operational efficiency. However, data privacy, algorithm interpretability, and ethical considerations must be addressed for responsible AI deployment in neonatal care. We highlight future directions, emphasizing interdisciplinary collaboration, adherence to reporting guidelines, and the need for further research to enhance AI reproducibility and clinical integration in the NICUs. The findings of this study support AI's potential for shaping neonatal health care.