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Machine Learning Approaches for the Prediction of Obesity using Publicly available genetic profiles.pdf

🔗 Source: researchonline.ljmu.ac.uk

📊 Size: 491 KB

📄 Pages: 8 pages

⬇️ Downloads: 55

Summary

The study uses data from the National Human Genome Research Institute Catalog and identifies genetic variants associated with obesity. The body mass index status of participants is divided into two classes, Normal Class and Risk Class. Dimensionality reduction tasks are performed to generate a set of principal variables, and various machine learning methods are applied to predict obesity. The results show that the support vector machine generated the highest area under the curve value of 90.5%. The study aims to contribute to the understanding of the genetic factors associated with obesity and to develop a predictive model for obesity risk.

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Description

The study uses data from the National Human Genome Research Institute Catalog and identifies genetic variants associated with obesity.

Technical Information

File Format: PDF
File Size: 491 KB
Pages: 8
Language: EN
Total Downloads: 55
Last Updated: 1 week ago

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