چکیده مقاله
Next Generation Sequencing NGS has transformed rare genetic disorder diagnosis, but the vast genomic data poses challenges Artificial Intelligence AI algorithms, particularly machine learning and deep learning models, enhance genetic understanding AIalgorithms can process large scale genomic information rapidly, enabling the identification of rare variants contributing to specificrare diseases based on their predicted impact on protein function, evolutionary conservation, or known disease associations Integrating data sources, AI aids in interpreting NGS data, uncovering genetic mechanisms By using AI in NGS analysis, cliniciansimprove diagnostic accuracy and efficiency for rare genetic disorders, enabling early and precise diagnoses and personalized treatmentstrategies AI driven results outperform manual analysis in accuracy, speed, complexity, scalability, and interpretability AI and opensourcetools like Exomiser excel in genetic data analysis, boosting the identification of disease causing genetic variations CombiningAI and manual analysis strengths enhances clinical diagnoses in rare genetic disorders
کلیدواژهها
نویسندگان
Kolsoum InanlooRahatloo
School of Biology, College of Science, University of Tehran, Tehran, Iran
شیوه ارجاع
InanlooRahatloo, Kolsoum,1403,AI-Driven Variant Prioritization in Rare Genetic Disorders: Enhancing Diagnostic Accuracy and Clinical Outcomes,1st International Biennial Conference of Artificial Intelligence and Data Science 2024,Bushehr
ارائهشده در
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