The Role of Artificial Intelligence in Genetic Disease Diagnosis: A Review

Genetic diseases are a diverse group of disorders caused by abnormalities in the human genome, and their diagnosis remains a major challenge in modern healthcare due to clinical heterogeneity, overlapping symptoms, and limitations in traditional diagnostic approaches. Despite advances in genomic technologies such as next-generation sequencing (NGS), whole-exome sequencing (WES), and whole-genome sequencing (WGS), the interpretation of complex genetic data and variants of uncertain significance continues to delay accurate diagnosis. The objective of this review is to examine the major challenges in genetic disease diagnosis and to explore the role of artificial intelligence (AI) and machine learning (ML) in improving diagnostic accuracy and efficiency. The findings of this study indicate that AI-based methods significantly enhance variant prioritization, genomic data interpretation, image-based phenotyping, and clinical decision support systems. Furthermore, the integration of AI with sequencing technologies improves the identification of disease-causing variants and supports precision medicine approaches. In conclusion, artificial intelligence has shown strong potential in transforming genetic disease diagnostics by reducing diagnostic delays and improving accuracy. However, challenges related to data quality, ethical considerations, and clinical implementation must be addressed to ensure safe and effective integration into healthcare systems.

کلیدواژه ها:

Genetic diseases ، Rare diseases ، Artificial intelligence ، Machine learning ، Next-generation sequencing ، Whole-exome sequencing ، Whole-genome sequencing ، Precision medicine