Decision making with artificial intelligence in the diagnosis of neonatal patients

Abstract

Natural language processing (NLP) is a branch of fabricated knowledge that focuses on the interaction between computers and human speech. Python is one of the most widely used programming dialects in handling common dialects due to its ease of use and the wide range of accessible libraries and devices. Through different widgets and libraries, Python allows engineers to work with content productively and successfully. Natural language management in Python has applications in a variety of areas, such as examining assumptions, automatic interpretation, and estimating research in social systems. In the field of neonatal medical services, the use of artificial intelligence (AI) and NLP can completely improve neonatal care by foreseeing possible dangers or complications during pregnancy, delivery, and postpartum care. Expandingly, AI can offer help in identifying intrinsic inconsistencies, formative disorders, and anticipating neonatal silent disintegration. Through AI calculations, silent weakening can be anticipated in neonatal clinics, allowing for faster and more accurate decisions. However, the use of AI in this context also raises moral, legitimate and social challenges that must be addressed with commitment and simplicity.