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Good nutrition is an essential component of life. Undernutrition is the root cause of death of over 3.5 million children under the age of five in India. To address this issue of malnutrition, though overarching national policy is desirable, it may not be effective if the root cause of malnutrition varies across regions of the country. In this context, the attempt made in this paper is two-fold. First,...
The rapid advancement of wearable devices and smartphones, allowed practitioners and specialists to keep track of physical, biological and behavioral activities. Nowadays, this self tracking, a.k.a. quantified self (QS), is widely used in big data science due to the large volume of data being generated from these devices. The wearable devices that are being used today for self-tracking can collect...
In upholding the Islamic way of life, effort to seek for moderation can be in the form of obesity prevention. Obesity is becoming the future burden of nations and actions have been taken to curb the problem of obesity. Most nations predict obesity based on the national past trend using data from population-based health surveys which are costly. Alternative method now points to data analytics which...
Various network relationships in many complex social systems can be described effectively by multilayer networks, but we find that there are interactions between individuals attributes and their social relationships by a principle of homophily, which hence impact the process of information spread and social influence in complex social systems. In order to integrate individuals relationships and attributes...
The human microbiome is a fundamental component of human physiology, with an estimated one-third of circulating metabolites being a product of the gut microbiota. Changes in the microbiome can trigger changes in human cellular activities, resulting in disease or contribute to its progression. Microbiota is considered to be a virtual "code" or a system emerging, with the properties that must...
Heart failure comes in the top causes of death worldwide. The number of deaths from heart failure exceeds the number of deaths resulting from any other causes. Recent studies have focused on the use of machine learning techniques to develop predictive models that are able to predict the incidence of heart failure. The majority of these studies have used a binary output class, in which the prediction...
Data mining techniques have been applied to many areas in the business world and our daily life, including healthcare and clinical health services. One of the mostly watched health problems is obesity and overweight, particularly for children and adolescents. In this paper, we try to find the most significant lifestyle risk factors associated with overweight and obesity among high school students...
Naïve Bayes is a data mining technique that has been used by many researchers for predictions in various domains. This paper presents a framework of a hybrid approach using Naïve Bayes for prediction and Genetic Algorithm for parameter optimization. This framework is a solution applied to the childhood obesity prediction problem that has a small ratio of negative samples compared to the positive samples...
Obesity is a common issue nowadays. The numbers of obese people are increasing every year. There are evidences that childhood obesity persists into adulthood. Predicting obesity at an early age is both useful and important because preventive measures and proper interventions can be applied if the children indicated a high risk of obesity. However, the prediction of childhood obesity is a difficult...
The primary objective of data mining and expert system provides good result for using knowledge base system. From the deep study, Apriori algorithm is a representation of an improved association rule mining algorithm, which helps to avoid the replication of same items. This proposed paper is an improved version of apriori algorithm that is focused on four features namely, First data preparation and...
Most common complex traits such as obesity, hypertension, diabetes, and cancers are known to be associated with multiple genes, environmental factors, and epistasis. Recently, the development of advanced genotyping technologies allows us to perform the genome-wide association studies (GWAS). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWAS...
The k-anonymity model has been introduced for protecting individual privacy. While focusing on membership disclosure, k-anonymity model fail to protect sensitive attribute disclosure. Different from the existing models of single sensitive attribute, extra associations among multiple sensitive attributes should be invested. In this paper, we propose a p-cover k-anonymity model to prevent both membership...
The mining of sequential patterns has been studied for several years, however, to our best knowledge, no study has considered the mining of sequential association rules despite such rules also providing valuable knowledge about many real applications. The sequential association rule represent that a set of items usually occur after a specific order sequence. In this paper, the concept of sequential...
In this paper we present data mining and its utilization for childhood obesity prediction. Data mining was widely used in many childhood obesity prediction systems. Predicting obesity at an early age is both useful and important because the number of obese patients is increasing while its main cause cannot yet be defined. The ability to predict childhood obesity will help early prevention. The purpose...
AMP-activated protein kinase (AMPK) is a metabolite- sensed protein kinase in various eukaryotes. The activated AMPK regulates important proteins which cause diabetes, obesity, metabolic aberrant, and also breast cancer. In this study, the yeast AMPK structure was used as a template to model the human AMPK structure. By homology modeling, the reliable AMPK structure was built, and the active binding...
The United States is facing an epidemic of childhood obesity, with obesity rates amongst children more than double what they were just 20 years ago. At the same time, research on the accessibility of healthy foods, especially in urban areas, has shown that certain populations are facing major barriers to a healthy diet. While there has been research on both the health consequences of childhood obesity...
Case based reasoning (CBR) is an approach for solving a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation. Selection and generation of cases are two important components of a CBR system. Obesity is one of the most significant public health problems facing the whole world. Children have been weighing progressively more since the 1970s,...
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