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1 August 2021 Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning
Saga Helgadottir, Stefano Romeo, Giovanni Volpe
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Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 118041C (2021) https://doi.org/10.1117/12.2593438
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States
Abstract
Familial hypercholesterolemia (FH) is the most common genetic disorder of lipid metabolism. The gold standard for FH diagnosis is genetic testing, available, however, only in selected university hospitals. Clinical scores – for example, the Dutch Lipid Score – are often employed as alternative, more accessible, albeit less accurate FH diagnostic tools. To overcome the limitations of these traditional methods and to obtain a more reliable approach to FH diagnosis we implement a “virtual” genetic test using machine-learning approaches.
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Saga Helgadottir, Stefano Romeo, and Giovanni Volpe "Virtual genetic diagnosis for familial hypercholesterolemia powered by machine learning", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 118041C (1 August 2021); https://doi.org/10.1117/12.2593438
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KEYWORDS
Genetics
Machine learning
Heart
Diagnostics
Evolutionary algorithms
Gold
Mode conditioning cables
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