Finding the most relevant features (SNPs) and their ranking for a specific disease under analysis, namely obesity, for each chromosome. 3. Forecast obesity ...
Big Data Analytics for Obesity Prediction. Authors. Ahsan Bilal, Alfredo ... This study analyzes genomic data related to prediction of human obesity.
Abstract. Feature selection (FS) is essential for the analysis of genomic datasets with millions of features. In such context, Big Data tools are paramount, ...
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This research paper explores the application of machine learning techniques in predicting obesity trends through big data analytics (BDA).
Sep 28, 2024 · The lifestyle and blood biochemical indicators of individuals are important bases for predicting the risk of obesity occurrence, researchers ...
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Jan 4, 2024 · The obesity prediction approach [2] uses algorithms to analyze vast volumes of data from many healthcare sectors to foresee and avoid obesity.
Sep 29, 2024 · This study explores the potential of machine-learning techniques to improve obesity risk prediction.
Machine learning may be a tool with the potential for obesity prediction. This study aims to review the literature on the performance of machine learning ...
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Nov 17, 2023 · To screen for predictive obesity factors in overweight populations using an optimal and interpretable machine learning algorithm.
The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes.