ASRIC Journal of Natural Sciences 2021 v1-i1
ISSN: 2795-3610
EISSN: 2795-3610
ASRIC Journal of Natural Sciences 2021 v1-i1
Abstract – The heart is an important organ in human beings. Because even a slight error might result in weariness or death, diagnosing and forecasting cardiac disorders requires increased precision, perfection, and accuracy. There are innumerable heart-related deaths, and the number is increasing significantly every day. To address the issue, researchers use a variety of data mining and machine learning approaches to evaluate massive amounts of complex medical data, assisting healthcare providers in the prediction of heart disease.
Published: 2021-12-04
Articles
Machine Learning Techniques for improving study of Heart Disease Prediction System
Abdelmegeid Amin Ali1, Ashraf Heikal2, Eman M. Anwar2,3, Shaimaa M Hussien2,3
The heart is an important organ in human beings. Because even a slight error might result in weariness or death, diagnosing and forecasting cardiac disorders requires increased precision, perfection, and accuracy. There are innumerable heart-related deaths, and the number is increasing significantly every day. To address the issue, researchers use a variety of data mining and machine learning a
Scaling Outcome Correlated Binary Big Data Using Estimates of Bivariate Dispersion Parameters
Ahmed M. M. Elsayed 1, Nevein N. Aneis1
Abstract— Dispersion parameter should be the unity in the case of the univariate Bernoulli data. But there may be some deviations if there is a sequence of the Bernoulli outcomes, that may lead to Binomial case. Over (lower) dispersion criterion is happened if the variance of actual response, var(y), is more (less) than the nominal variance as a function of the mean, var(μ). This paper presents th
Heavy Metals analysis in Koche River and Associated Impacts on the Adjacent Community, Tatek Industrial Zone, Ethiopia
Mathewos Temesgen1, Tegenu Alemu2
This study was determining the levels of some heavy metals in Koche River and the associated impacts on the adjacent community, Tatek Industrial Zone, Ethiopia. Water samples were taken from 12 sampling sites. Questionnaire survey, focus group discussion, key informant interview and secondary data sources were also used to collect additional data. The heavy metals were determined using flame AAS.
Water Scarcity - the Driving Force of Underdevelopment in Rural Areas of Developing Countries
Sasanya, Blessing Funmbi1, Adesogan, Sunday Olufemi2
Water scarcity results to socio-economic problems and health complications. Attempts at solving water scarcity problems, such as groundwater extraction and stream damming, are not easily attainable in some locations due to geological formations and hydrologic features. The aim of this study is to investigate health and socioeconomic effects, causes and remedy of water scarcity in rural communit
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