Image: Researchers create one-of-a-kind disease prediction software (photo courtesy of Rutgers Health)
Currently, there are no artificial intelligence (AI) or machine learning tools to explore and interpret the entire human genome, especially for non-experts. Now, first-of-its-kind software combines artificial intelligence and machine learning approaches to understand the importance of specific genomic biomarkers for predicting disease in humans.
IntelliGenes software, created by researchers at Rutgers Health (New Brunswick, NJ, USA), combines traditional statistical methods with advanced machine learning algorithms to create personalized predictions for patients and provide visual representations of biomarkers important for disease prediction. IntelliGenes was designed so that the platform can be used by anyone, including students or those who lack advanced bioinformatics knowledge or access to high-performance computers.
In one study, researchers demonstrated how a wide range of users can use IntelliGenes to analyze clinical and multigenomic data. In another study, researchers used IntelliGenes to discover new biomarkers and predict cardiovascular disease with high accuracy. The researchers also tested the software using Amarel, a high-performance computing cluster run by Rutgers’ Office of Advanced Computing Research.
“IntelliGenes has the potential to facilitate personalized early detection of common and rare diseases in individuals, and also opens up opportunities for broader research that ultimately leads to new interventions and treatments,” said Zeeshan Ahmed, lead author of the study and faculty member at Rutgers Institute. in Public Health, Health Policy, and Aging Research (IFH).
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Rutgers Health
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