New AI tool links genetic mutations to diseases with improved accuracy
Researchers have developed an artificial intelligence tool that not only detects disease-causing genetic variants but also predicts the types of diseases they may lead to, potentially accelerating diagnosis and treatment.
Scientists at the Icahn School of Medicine at Mount Sinai have created an AI tool called Variant to Phenotype (V2P) that can identify genetic mutations and predict the diseases they may cause, bolstering the field of genetic diagnostics.
The V2P method is designed to accelerate diagnosis and facilitate the discovery of new treatments for complex and rare diseases by comprehensively interpreting genomic data, surpassing the limitations of traditional techniques that often focus solely on mutation detection without predicting phenotypic effects.
This innovation could enhance clinical decision-making by linking specific genetic variants directly to disease risk, helping clinicians prioritise variants for further study and informing patients about likely outcomes sooner.
The findings were published online in Nature Communications, marking a notable advancement in how AI can support precision medicine and research for rare diseases.
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