AI Breakthrough Enhances Diagnosis of Genetic Eye Disorders
Tokyo researchers have developed an AI-based system to automate sister chromatid exchange counting, improving diagnosis of Bloom syndrome and other DNA-related eye disorders.
Chromosomes carry the DNA blueprint essential for life. During cell division, sister chromatids are formed, which normally remain intact. DNA damage can trigger exchanges between sister chromatids, which may indicate serious genetic disorders such as Bloom syndrome, associated with higher cancer risk.
Traditionally, counting these exchanges relied on labor-intensive microscopic examination, dependent on specialist expertise. A research team from Tokyo Metropolitan University, led by Professors Kyoshi Nishikawa and Kan Okubo, developed an AI algorithm that identifies chromosomes, detects exchange sites, and counts them automatically, achieving 84.1% accuracy comparable to manual methods.
Automating Bloom Syndrome Diagnosis
This AI tool enables faster, more objective analysis of chromatid exchanges and paves the way for broader applications in genetic eye disorder diagnostics. The team continues to train the algorithm on larger datasets to further improve accuracy, potentially revolutionizing clinical assessments.
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