Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction

Cataloged from PDF version of thesis.

Manylion Llyfryddiaeth
Prif Awduron:	Oishi, Fayza Rezwana, Al Mahadi, Mehnaj, Parvez, Omar Bin
Awduron Eraill:	Arif, Hossain
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2020
Pynciau:	Machine learning algorithms Coronary Heart Disease (CHD) Healthcare Chi Squared Technique Machine learning Computer algorithms Machine learning > Mathematical models
Mynediad Ar-lein:	http://hdl.handle.net/10361/13694

id	10361-13694
record_format	dspace
spelling	10361-136942022-01-26T10:10:28Z Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction Oishi, Fayza Rezwana Al Mahadi, Mehnaj Parvez, Omar Bin Arif, Hossain Department of Computer Science and Engineering, Brac University Machine learning algorithms Coronary Heart Disease (CHD) Healthcare Chi Squared Technique Machine learning Computer algorithms Machine learning--Mathematical models Cataloged from PDF version of thesis. Includes bibliographical references (pages 33-34). This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2018. The world of Machine Learning is expanding everyday through its implementations in modern day healthcare. Researchers have sketched out many ways to implement Machine Learning algorithms and droned into ways to make them work in their utmost efficiencies. As there will always be the need for healthcare in the world, we believe that there will always be a need of comparison between Machine Learning algorithms in terms of their performance and relevance to make healthcare more reliable through Machine Learning. For this study, we have picked up the most commonly used Machine Learning algorithms, Logistic Regression, Support Vector Machine, Decision Tree and Random Forest to produce a comparative analysis on a dataset of Framingham Heart Study which is dedicated to the prediction of risk of Coronary Heart Disease (CHD). We have used a combination of Data Preprocessing and Feature Selection methods, namely The Row Elimination method and Recursive Feature Elimination respectively. To understand the impact of each prevailing features in the dataset on the target feature, we have applied the Chi Squared Technique which is a highly recommended technique when it comes to classification problems. To compare and analyze performance of the algorithms, we applied concepts of the Confusion Matrix, Precision, Recall and F1 Scores; we have plotted ROC curves using Sensitivity and Specificity scores to categorize the algorithms’ behavior. We have found out that the highest average accuracy in our study was given by the Logistic Regression algorithm (83.9%) while the other algorithms have come fairly close. Fayza Rezwana Oishi Mehnaj Al Mahadi Omar Bin Parvez B. Computer Science 2020-02-02T04:47:45Z 2020-02-02T04:47:45Z 2018 2018-12 Thesis ID 18201215 ID 13201076 ID 18241031 http://hdl.handle.net/10361/13694 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 34 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Machine learning algorithms Coronary Heart Disease (CHD) Healthcare Chi Squared Technique Machine learning Computer algorithms Machine learning--Mathematical models
spellingShingle	Machine learning algorithms Coronary Heart Disease (CHD) Healthcare Chi Squared Technique Machine learning Computer algorithms Machine learning--Mathematical models Oishi, Fayza Rezwana Al Mahadi, Mehnaj Parvez, Omar Bin Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
description	Cataloged from PDF version of thesis.
author2	Arif, Hossain
author_facet	Arif, Hossain Oishi, Fayza Rezwana Al Mahadi, Mehnaj Parvez, Omar Bin
format	Thesis
author	Oishi, Fayza Rezwana Al Mahadi, Mehnaj Parvez, Omar Bin
author_sort	Oishi, Fayza Rezwana
title	Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
title_short	Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
title_full	Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
title_fullStr	Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
title_full_unstemmed	Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
title_sort	comparative analysis between machine learning algorithms in efficiency of coronary heart disease (chd) prediction
publisher	Brac University
publishDate	2020
url	http://hdl.handle.net/10361/13694
work_keys_str_mv	AT oishifayzarezwana comparativeanalysisbetweenmachinelearningalgorithmsinefficiencyofcoronaryheartdiseasechdprediction AT almahadimehnaj comparativeanalysisbetweenmachinelearningalgorithmsinefficiencyofcoronaryheartdiseasechdprediction AT parvezomarbin comparativeanalysisbetweenmachinelearningalgorithmsinefficiencyofcoronaryheartdiseasechdprediction
_version_	1814307720967225344

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction

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