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A survey on Machine Learning Classifiers and Big data for Accurate and Reliable Heart Disease Pre-diagnosis

Srikanth Meda, Associate Professor, Dept. of CSE, R.V.R. J.C. College of Engineering, Guntur
2019 International Journal of Advanced Research in Big Data Management System  
Today's medical diagnosis systems, which are utilizing different data mining techniques like Decision Trees (DT), Support Vector Machines (SVM), Naï ve Bayes (NB), Fuzzy Logics and K-Nearest Neighbor (  ...  Most popular data mining techniques, which are participating in medical data processing with high accuracy are selected and cross referenced by our proposed framework to overcome uncertainty and imprecision  ...  These mathematical variables are most convenient data values for manipulations and decision making by machine learning techniques.  ... 
doi:10.21742/ijarbms.2019.3.2.04 fatcat:c2jqrrpmv5hxpew6fmob7lcz6i

Medical Expert System using Data mining and Machine Learning

Suhas A Bhyratae, Sumukha J Sharma, Tarun Kumar K
2019 IJARCCE  
In this paper, data mining methods namely, Naive Bayes and J48 algorithms are compared for testing their accuracy and performance on the training medical datasets.  ...  This paper highlights the application of classifying and predicting a specific disease by implementing the operations on medical data generated in the field of medical and healthcare.  ...  Propelled data mining techniques are used to discover knowledge in database and for medical research, particularly in Heart disease prediction. learning, Meta supervised learning, feature selection, data  ... 
doi:10.17148/ijarcce.2019.8320 fatcat:4a4qg7szhrf2pf6ubjav2ojk5a

Overcoming "Big Data" Barriers in Machine Learning Techniques for the Real-Life Applications

Ireneusz Czarnowski, Piotr Jedrzejowicz, Kuo-Ming Chao, Tülay Yildirim
2018 Complexity  
The editors hope that the presented research results will be of value to the scientific community working in the field of Big Data, data science, machine learning, analysis of complex data, data mining  ...  Presented results are also addressed for other researchers who are currently or will be in the future implementing different data analysis tools trying to solve the real-life problems.  ...  Czarnowski and P. Jędrzejowicz proposes an approach to data reduction for learning from Big Data sets by integrating stacking, rotation, and agent population learning techniques.  ... 
doi:10.1155/2018/1234390 fatcat:x5eqcf2nyvebhda3ag5i7a2niy

Analysis Of Single And Hybrid Data Mining Techniques For Prediction Of Heart Disease Using Real Time Dataset

Syed Ahmed Yasin, Dr P.V.R.D.Prasad Rao
2018 International Journal of Engineering & Technology  
Data mining and healthcare has strong relations as data mining is a process where we can analyze enormous set of data and after extraction meaning of data can be understood.  ...  so that they can answer whether to apply single or compound data mining technique.  ...  Raja Rajeswari, Members, Doctorial committee, KLEF for their valuable guidance and constant support throughout my work.  ... 
doi:10.14419/ijet.v7i2.32.13536 fatcat:av55jr5rdnfoxlodyxo6p7fm6i

A Review of Denoising Medical Images Using Machine Learning Approaches

Prabhpreet Kaur, Gurvinder Singh, Parminder Kaur
2018 Current Medical Imaging Reviews  
The problem faced by the researchers during image denoising techniques and machine learning applications for clinical settings have also been discussed.  ...  For fast and computational results the radiologists are using the machine learning methods on MRI, US, X-Ray and Skin lesion images.  ...  Now-adays, the interests of the radiologists are attracted towards the medical data mining for patience care. Medical data mining and image denoising is the state of art challenge for researchers.  ... 
doi:10.2174/1573405613666170428154156 pmid:30532667 pmcid:PMC6225344 fatcat:tyfmwr7dszh2paqx7m4ktue4oi

Heart Disease Prediction using Machine Learning Techniques

Devansh Shah, Samir Patel, Santosh Kumar Bharti
2020 SN Computer Science  
Researchers apply several data mining and machine learning techniques to analyse huge complex medical data, helping healthcare professionals to predict heart disease.  ...  Data mining is a commonly used technique for processing enormous data in the healthcare domain.  ...  This article is part of the topical collection "Advances in Computational Approaches for Artificial Intelligence, Image Processing, IoT and Cloud Applications" guest edited by Bhanu Prakash K N and M.  ... 
doi:10.1007/s42979-020-00365-y fatcat:cvldc6jdgrfgje7wfjabgis3nu

Current Developments in Machine Learning Techniques in Biological Data Mining

Gerard G Dumancas, Indra Adrianto, Ghalib Bello, Mikhail Dozmorov
2017 Bioinformatics and Biology Insights  
of machine learning techniques in mining biological data.  ...  in the use of machine learning methods in knowledge discovery and data mining to generate models of biological implications.  ...  sequencing data analysis (DNA and RNA sequencing), network modeling, data mining, and machine learning.  ... 
doi:10.1177/1177932216687545 pmid:28469415 pmcid:PMC5390918 fatcat:bmxrd3ymqrcmhofko76gl25fka

Analysis And Detection of Diabetes Using Data Mining Techniques – Efficiency Comparison

G. Ramadevi, Srujitha Yeruva, P. Sravanthi, P. Eknath Vamsi, S. Jaya Prakash
2021 International Journal of Scientific Research in Science and Technology  
Data mining techniques are very much useful in analyzing medical data to achieve meaningful and practical patterns.  ...  The objective of data mining techniques used is to design an automated tool that notifies the patient's treatment history disease and medical data to doctors.  ...  Designing of automated diabetic detection uses machine learning and data mining techniques. II.  ... 
doi:10.32628/cseit217425 fatcat:4o5nng3v6bbvjdjidqtybel3ni


Hafiz Gulfam Ahmad, Ghazi University, Muhammad Jasim Shah, Emerson University
2021 Azerbaijan Journal of High Performance Computing  
We compare and contrast several machine learning methods, such as KNN, ANN, Decision Tree, SVM, and Random Forest. We looked at 918 observations with several features related to heart disease.  ...  Our research is motivated by the desire to predict cardiovascular diseases based on data mining that can be valuable to medical centers.  ...  In our research, we employ data mining to forecast cardiac diseases. Machine learning, databases, and statistical analysis are already used in data mining.  ... 
doi:10.32010/26166127.2021. fatcat:6gnx7indjjdwxd7cryob2sewbu

A Survey on Prediction Techniques of Heart Disease using Machine Learning

Mangesh Limbitote, Pimpri Chinchwad College of Engineering ,Pune
2020 International Journal of Engineering Research and  
Furthermore, an in-depth analysis of the most relevant machine learning techniques available on the literature for heart disease prediction is briefly elaborated.  ...  This data is analysed on regular basis. In this review, an overview of the heart disease and its current procedures is firstly introduced.  ...  the analysis of large and complex data.  ... 
doi:10.17577/ijertv9is060298 fatcat:tmb6whdmp5eozi6ddg4dgyfepe

A Survey on Efficient use of Data Mining and Machine Learning in Healthcare Applications

Aishwarya Hastak, Prangana Kashyap, Nupur Surana, Bhushan Inje
2021 Zenodo  
Massive amounts of data have been collected in the healthcare industry over the past years using the EHR systems; data analysis with the help of machine learning models can help in making predictions and  ...  The use of various machine learning algorithms and data mining tools and their efficiencies also have been studied. The accuracy of various algorithms used in early disease prediction is compared.  ...  Applications and efficiencies of various machine learning algorithms and data mining tools have been studied.  ... 
doi:10.5281/zenodo.5139536 fatcat:y3p6txlxrvdnhl5gbow6aofhrm

Comparative Analysis of Data Mining Techniques in Sphere of Medical Science

Divya Arora, Karuna Middha
2018 International Journal of Computer Applications  
The goal of the paper is to study techniques, algorithms and accuracy of results since 2011 from selected set of papers for the diagnosis of two diseases i.e. Heart attacks and Liver Disorder.  ...  To use it optimally, Data mining field is gaining popularity in this field of research due to its various approaches or techniques to mine the effective data from the huge set in an efficient way.  ...  Weka Weka primarily used for data mining tasks, is a collection of machine learning algorithms.  ... 
doi:10.5120/ijca2018916658 fatcat:ez6jkf46gfg7vd2ys7c2l2ixi4

A Review on Data mining from Past to the Future

Venkatadri. M, Lokanatha C. Reddy
2011 International Journal of Computer Applications  
Advancements in Statistics, Machine Learning, Artificial Intelligence, Pattern Recognition and Computation capabilities have evolved the present day's data mining applications and these applications have  ...  Data mining is the knowledge discovery process by analyzing the large volumes of data from various perspectives and summarizing it into useful information.  ...  The important data mining technique used for hypertext and hypermedia data are Classification (supervised learning), Clustering (unsupervised learning).  ... 
doi:10.5120/1961-2623 fatcat:6w4qyny3ibcuvp732x47f2f344


Mohith N Raate, Dr. Kiran V
2021 International Journal of Engineering Applied Sciences and Technology  
This technique involves two most successful data mining tools, Support vector machine and Principal component analysis.  ...  Data mining techniques have been widely used in clinical decision support systems for prediction and diagnosis of various diseases with good accuracy.  ...  METHODOLOGY Data mining techniques are used to explore, analyse extract medical data using complex algorithms in order to discover unknown patterns.  ... 
doi:10.33564/ijeast.2021.v06i05.026 fatcat:ea6mqmhcfzc2lc5m3d5pf7xuce

A Framework for Medical Images Classification Using Soft Set

Saima Anwar Lashari, Rosziati Ibrahim
2013 Procedia Technology - Elsevier  
For these several medical imaging modalities and applications based on data mining techniques have been proposed and developed.  ...  As a result, a new framework for medical imaging classification consisting of six phases namely: data acquisition, data pre-processing, data partition, soft set classifier, data analysis and performance  ...  Acknowledgements The authors would like to thank Ministry of Higher Education (MOHE) and Universiti Tun Hussein Onn Malaysia (UTHM) for supporting this research under the Fundamental Research Grant Scheme  ... 
doi:10.1016/j.protcy.2013.12.227 fatcat:opxhly23ivdzjksqk7gylnde3q
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