CONTRIBUTIONS TO THE STUDY OF BIG DATA ANALYTICS - C, Mithra
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This book explores the genetic adaptations of populations living in high altitude environments and the diseases they face. The researcher uses text mining and network analysis to identify the gene networks responsible for high altitude diseases. The author proposes a machine learning algorithm named Random Forest to predict miRNA-disease association using five modules: preprocessing, data analysis, feature extraction, dimensionality reduction, and prediction. The methodology is evaluated using precision, recall, F-measure, and accuracy. This research aims to improve the identification of…mehr

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Produktbeschreibung
This book explores the genetic adaptations of populations living in high altitude environments and the diseases they face. The researcher uses text mining and network analysis to identify the gene networks responsible for high altitude diseases. The author proposes a machine learning algorithm named Random Forest to predict miRNA-disease association using five modules: preprocessing, data analysis, feature extraction, dimensionality reduction, and prediction. The methodology is evaluated using precision, recall, F-measure, and accuracy. This research aims to improve the identification of disease genes from vast amounts of genetic data and provide a powerful tool for diagnosing, progressing, and treating human diseases.
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Autorenporträt
Mithra C é bolseira de doutoramento em Ciência e Engenharia Informática (CSE) na Universidade de Annamalai, Índia. Tem um mestrado em CSE - Big Data da Universidade de Anna (CEG), um MBA da Universidade de Annamalai e uma licenciatura em CSE da Faculdade de Engenharia de Jeppiaar. As suas áreas de interesse incluem aprendizagem automática, extração de dados, análise de dados e engenharia de software.