Artificial Intelligence and medical specialties: support or substitution?

Abstract

The rapid advancement of artificial intelligence (AI) in healthcare has spurred extensive debate regarding its potential to replace human expertise across various medical specialties. This narrative review critically examines the integration of AI within diverse medical specialties to discern its role as a substitute or supporter. The analysis encompasses AI's impact on diagnostic precision, treatment planning, and patient care. Although AI systems have demonstrated remarkable proficiency in tasks reliant on data analysis and pattern recognition, they fall short in areas necessitating nuanced decision-making, empathetic communication, and the application of human medical expertise in diagnosis and treatment planning. The rapid evolution of AI applications within medical specialties is propelled by the swift advancements in both hardware and software technologies, fostering a dynamic synergy that continues to redefine the boundaries of precision and efficiency in healthcare delivery. While AI demonstrates remarkable capabilities in automating tasks, it is underscored that its integration in complex domains necessitates a balanced approach that preserves the indispensable contributions of human activity.

Keywords: artificial intelligence; healthcare systems; machine learning; medical specialties.