Exploring the Impact of AI on Healthcare Diagnostics: A Systematic Review

Abstract

The introduction of Artificial Intelligence (AI) into healthcare, particularly in the realm of diagnostics, has brought both excitement and concern. This systematic review examines AI-driven diagnostic systems, analyzing their ability to detect diseases at earlier stages compared to conventional methods. We reviewed 75 studies, focusing on applications in imaging, pathology, and genomics. The results reveal a significant improvement in diagnostic accuracy, particularly in radiology, dermatology, and oncology, where machine learning models demonstrated superior precision in identifying abnormalities. However, the review also identifies key challenges, including issues of data privacy, algorithmic bias, and the need for better integration of AI tools into existing healthcare workflows. Future work must focus on creating regulatory frameworks and standards for AI use in medical settings.