الذكاء الاصطناعي في التشخيص المبكر: إمكانات هائلة وتحديات حرجة

Abstract

This review investigates the transformative potential of artificial intelligence (AI) in early disease diagnosis, analyzing both its significant benefits and ongoing challenges. The paper synthesizes the results of recent studies (2017–2025) demonstrating the exceptional ability of AI, particularly through deep learning, to analyze complex medical data—including radiological images, electronic health records, and genomic data—to detect diseases such as cancer, cardiovascular disease, and neurological disorders at stages often preceding the onset of clinical symptoms. Evidence suggests that diagnostic performance is comparable to, and in some cases superior to, that of healthcare professionals, thereby enhancing accuracy and reducing errors. Furthermore, the review explores emerging applications in the fields of genomics, wearable technology, and generative AI. However, the widespread clinical integration of AI faces significant hurdles, including the "black box" problem of model interpretation, issues of data quality and bias, and critical ethical and legal concerns related to liability and data privacy. The conclusion emphasizes that the optimal path forward requires a collaborative partnership between humans and artificial intelligence, where AI serves as a powerful decision-support tool that enhances, but does not replace, the role of physician judgment and experience, to ensure responsible and effective adoption in routine medical practice.