Artificial intelligence in disease diagnosis: balancing concerns and reliance on outcomes

Abstract

This study explores the role of Artificial Intelligence (AI) in disease diagnosis, highlighting its accuracy, limitations, and associated concerns. Findings indicate an average diagnostic accuracy of 92%, but challenges such as algorithmic bias and the need for transparency remain significant. The research underscores the importance of integrating AI with clinical judgment and emphasizes strategies for effective implementation in healthcare settings.