scholarly journals RESEARCH ON MACHINE LEARNING ALGORITHM ON HEART DISEASE PREDICTION

2020 ◽  
Vol 5 (2) ◽  
pp. 489-493
Author(s):  
Yash Raj Tripathi ◽  
Shruti Gupta ◽  
Shubham Mishra
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Learning Algorithm ◽  
Disease Prediction ◽  
Machine Learning Algorithm

scholarly journals Data mining techniques with machine learning algorithm to predict patients of heart disease

2021 ◽  
Vol 1088 (1) ◽  
pp. 012035
Author(s):  
Mulyawan ◽  
Agus Bahtiar ◽  
Githera Dwilestari ◽  
Fadhil Muhammad Basysyar ◽  
Nana Suarna
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Heart Disease ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Data Mining Techniques

scholarly journals Heart Disease Prediction

2018 ◽  
Vol 7 (3.12) ◽  
pp. 750
Author(s):  
S Vinothini ◽  
Ishaan Singh ◽  
Sujaya Pradhan ◽  
Vipul Sharma
Keyword(s):  
Heart Disease ◽  
Decision Tree ◽  
Clustering Algorithm ◽  
Learning Algorithm ◽  
Disease Prediction ◽  
Machine Learning Algorithm ◽  
Data Set ◽  
Logistics Regression ◽  
Learning Technique ◽  
Work Integration

Machine learning algorithm are used to produce new pattern from compound data set. To cluster the patient heart condition to check whether his /her heart normal or stressed or highly stressed k-means clustering algorithm is applied on the patient dataset. From  the results of clustering ,it is hard to elucidate and to obtain the required conclusion from these clusters. Hence another algorithm, the decision tree, is used for the exposition of the clusters of . In this work, integration of decision tree with the help of k-means algorithm is aimed. Another learning technique such as SVM and Logistics regression is used. Heart disease prediction results from SVM and Logistics regression were compared. 

Disease Prediction using Naïve Bayes - Machine Learning Algorithm

2021 ◽  
Vol 6 (4) ◽  
pp. 17-22
Author(s):  
Chandrasekhar Rao Jetti ◽  
Rehamatulla Shaik ◽  
Sadhik Shaik
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Healthcare System ◽  
Naive Bayes ◽  
Learning Algorithm ◽  
Naïve Bayes ◽  
Disease Prediction ◽  
Machine Learning Algorithm ◽  
Data Mining Techniques ◽  
Smart Healthcare

It can occur on many occasions that you or a loved one requires urgent medical assistance, but they are unavailable due to unforeseen circumstances, or that we are unable to locate the appropriate doctor for the care. As a result, we will try to incorporate an online intelligent Smart Healthcare System in this project to solve this issue. It's a web-based programmed that allows patients to get immediate advice about their health problems. The aim of the smart healthcare system is to create a web application that can take a user's symptoms and predict diseases, as well as serve as an online consultant for various diseases. We created an expert system called Smart Health Care System, which is used to make doctors' jobs easier. A machine examines a patient at a basic level and recommends diseases that may be present. It begins by inquiring about the patient's symptoms; if the device is able to determine the relevant condition, it then recommends a doctor in the patient's immediate vicinity. The system will show the result based on the available accumulated data. We're going to use some clever data mining techniques here. We use several intelligent data mining techniques to guess the most accurate illness that could be associated with a patient's symptoms, and we use an algorithm (Naive Bayes) to map the symptoms with potential diseases based on a database of many patients' medical records. This system not only makes doctors' jobs easier, but it also benefits patients by getting them the care they need as soon as possible. Keywords: Disease Prediction, Naïve Bayes, Machine Learning Algorithm, Smart Healthcare System.

scholarly journals Retraction: Machine Learning based Classification for Heart Disease Identification (J. Phys.: Conf. Ser 1916 012174)

2021 ◽  
Vol 1916 (1) ◽  
pp. 012237
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Cell Biology ◽  
Learning Algorithm ◽  
Distributed Processing ◽  
Disease Classification ◽  
Disease Prediction ◽  
Similar Time ◽  
Link Type ◽  
Processing Network

This article has been retracted by IOP Publishing following an allegation that this article contains text overlap from multiple unreferenced sources [1, 2]. IOP Publishing has investigated and agree the article constitutes plagiarism. IOP Publishing also expresses concern regarding a number of nonsensical phrases used in the article, which suggests the article may have been created at least partly by artificial intelligence or translation software. IOP Publishing also notes sections of this article were published in multiple other journals at a similar time [3, 4, 5, 6], by different author groups. These issues all bring the legitimacy of this article into serious doubt. The authors have not responded to confirm whether they agree or disagree to this retraction. IOP Publishing wishes to credit Problematic Paper Screener [7] for bringing some of these issues to our attention. 1. "Machine learning" Wikipedia, Wikimedia Foundation,https://en.wikipedia.org/wiki/Machine_learning 2. "Cardiovascular disease" Wikipedia, Wikimedia Foundation, https://en.wikipedia.org/wiki/Cardiovascular_disease 3. Sukanth, N. et al., 2021. Heart Disease Classification using Machine Learning Algorithm. International Journal of Innovative Research in Computer and Communication Engineering, 9(3), pp.1108-1114. 4. Karthikeyan, N. et al., 2021. Machine learning based classification models for heart disease prediction. Journal of Physics: Conference Series, 1916. 5. Priyadharshini, K. et al., 2021. Coronary Infarction Prediction Using Correlation Analysis aspects based on Parallel Distributed Processing Network. Annals of the Romanian Society for Cell Biology, 25(4), pp.2864-2869. 6. Vennila, V. et al., 2021. Enhanced Deep Learning Assisted Convolutional Neural Network for Heart Disease Prediction. Annals of the Romanian Society for Cell Biology, 25(3), pp.8467-8474. 7. Cabanac G, Labbe C, Magazinov A, 2021, arXiv:2107.06751v1 Retraction published: 17 December 2021

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