Artificial Intelligence (AI) Improves Patient Outcomes in Neonatal Intensive Care Units: Challenges and Future Directions

Abstract

BackgroundArtificial intelligence (AI), motivated by its potential to enhance patient outcomes and assist professional judgments, is poised to significantly transform medicine, as evidenced by the notable rise in research studies, particularly in critical care medicine [1].This expansion is reflected in the growing number of clinical studies on AI-related themes [2].Additionally, generative AI is becoming more popular in healthcare settings, especially with large language models (LLMs) like ChatGPT, which help with communication and documentation duties and support decision-making.Healthcare professionals' initial opinions of ChatGPT in pediatric critical care emphasize both its advantages and disadvantages [3].Despite the challenges in research caused by ethical and practical issues, AI may assist doctors with diagnosis, prognostics, and treatment in pediatric intensive critical care to enhance patient outcomes [4].However, a lot more work needs to be done before the results of AI research are used at the patient's bedside and become a true clinical benefit.The influence of AI models in the actual world is currently limited because less than 2% of them make it past the prototype stage [5].Since most of the patients in this research are adults and bias are a significant issue for AI models, it is unclear how these results relate to pediatric populations.Each group has distinct clinical needs, assessments, and treatment approaches due to the notable variations in disease incidence, presentation, outcomes, and prognosis among youngsters [6].Therefore, creating AI models especially suited to pediatric care is imperative to closing this gap. Clinical Influence and Readiness of AIEven though some experts believe AI will revolutionize healthcare in the future, most new AI technologies have not yet been adopted by the larger medical community.Not every

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