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All Journal Journal of Robotics and Control (JRC) Review of Islamic Social Finance and Entrepreneurship
Ahmed, Mohammed
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Religion Aerospace Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Mechanical Engineering Social Sciences

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Heart Disease Prediction Using Hybrid Machine Learning: A Brief Review Ahmed, Mohammed; Husien, Idress
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21606

Abstract

Cardiovascular disease is a widespread and potentially fatal condition that requires proactive preventive measures and efficient screening approaches on a global scale. To tackle this issue, recent studies have investigated novel machine-learning frameworks that propose to diagnose and forecast cardiovascular disease by capitalizing on enormous datasets and predictive patterns linked to this condition. The research contribution is a thorough examination and implementation of ensemble learning and other hybrid machine-learning techniques for heart disease prediction. By employing ensemble learning on datasets including The Cleveland heart disease dataset and The IEEE Dataport heart diseases dataset such as age, chest pain type, blood pressure, blood glucose level, ECG in rest, heart rate, and four types of chestpain. To predict heart disease, our methodology integrates numerous machine learning models. By capitalising on the merits of specific algorithms while addressing their drawbacks, this approach yields a predictive model that is more resilient. The findings of our research exhibit encouraging outcomes in the realm of heart disease prediction, attaining enhanced precision and dependability in contrast to discrete algorithms. Through the utilisation of ensemble learning, we successfully discerned predictive patterns that are linked to heart disease, thereby augmenting the capabilities of diagnostics. In summary, the findings of our study emphasise the considerable potential of ensemble techniques within the realm of machine learning for the advancement of cardiac disease prediction. By providing a more dependable method for rapid diagnosis and prognosis of cardiac disease, this strategy has substantial ramifications for healthcare practices.
Public entrepreneurship, municipal performance, and political capacity's moderating role in Niger state Ahmed, Mohammed; Umar, Mohammed-Bello Habiba
Review of Islamic Social Finance and Entrepreneurship Volume 3 Issue 2, 2024
Publisher : Center for Islamic Economics and Development Studies [P3EI]

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/RISFE.vol3.iss2.art4

Abstract

Purpose – This study investigates the moderating role of political capacity (PC) in the relationship between public entrepreneurship (PE) and local government performance (LGP) in Niger State, Nigeria, using structural equation Modelling (SEM).Methodology – This study is a quantitative research based on a sample of 1,396 employees from four local government areas in Niger State, Nigeria. A non-probability sampling method was utilized, and the data were analyzed using STATA version 17 to obtain descriptive statistics, perform a normality test, assess factor loadings, and conduct correlation and SEM analyses.Findings – The analysis revealed that the mean values of public entrepreneurship, political capacity, and local government performance were low. The SEM analysis found that political capacity significantly moderates the relationship between public entrepreneurship and local government performance and establishes a direct relationship between public entrepreneurship, political capacity, and the performance of local governments.Implications – This study suggests that political capacity should be considered in the administration of local governments, as it can lead to more effective management of municipalities.Originality – No previous research has explored the relationship between political capacity, public entrepreneurship, and local government performance using SEM in the context of local government administration.
Co-Authors Husien, Idress Umar, Mohammed-Bello Habiba