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Classification and Prediction Model using Hybrid Technique for Medical Datasets

Raghavendra S., Indiramma M.
2015 International Journal of Computer Applications  
Classification and prediction of medical datasets poses real challenges in Medical Data Mining.  ...  Medical data mining is an important area of Data Mining and considered as one of the important research field due to its application in healthcare domain.  ...  Pattern Recognition and Data Mining techniques are used in risk prediction of cardiovascular medicine. The data to be modeled is classified using classification Data Mining technique.  ... 
doi:10.5120/ijca2015906382 fatcat:ubo3lokhhvc4xdbphfqrj3dsym

A Survey of Predicting Heart Disease

M Preethi, J Selvakumar
2020 JOIV: International Journal on Informatics Visualization  
This paper describes various methods of data mining, big data and machine learning models for predicting the heart disease.  ...  Data mining and machine learning plays an important role in building an important model for medical system to predict heart disease or cardiovascular disease.  ...  The hybrid approach is combination of random forest and linear method. The dataset and subsets of attributes were collected for prediction.  ... 
doi:10.30630/joiv.4.2.365 fatcat:62uoyms37vfrpguu2gdsdyl3kq

A Survey of Data Mining Techniques on Risk Prediction: Heart Disease

G. Purusothaman, P. Krishnakumari
2015 Indian Journal of Science and Technology  
Comparison of classification techniques in Data mining to find the best technique for creating risk prediction model of heart disease at minimum effort.  ...  This paper provides a quick and easy understanding of various prediction models in data mining and helps to find best model for further work.  ...  The records with irrelevant data were removed from data warehouse before mining process occurs. Data mining classification technology consists of classification model and evaluation model.  ... 
doi:10.17485/ijst/2015/v8i12/58385 fatcat:3a2ko6u3zng35pmp4nv52356we

Ensemble Classification Algorithms for Breast Cancer Prognosis

In this paper, we used Data mining classification algorithms to find the presence of breast cancer whether it is benign or malignant and analysis is done on the basics of accuracy and time taken in build  ...  The data is collected from WISCONSIN of UCI machine learning Repository, which includes patient's samples. The dataset undergoes different algorithm with and without feature selection.  ...  Hybrid Naïve Bayes and J48 Voting (Voting for the classification and Averaging for the regression techniques) is the concept of prediction of data mining which combines the classification from different  ... 
doi:10.35940/ijitee.b6886.129219 fatcat:eqvt43so2jhl5ej5lb7szidxzu


R. Ramya
2017 International Journal of Advanced Research in Computer Science  
Hence DRN hybrid can be used to predicting autism using the historical dataset.  ...  DRN hybrid model is implemented in Rapid Miner tool to find the Accuracy, Precision, recall, Classification error and Executed time.  ...  Hence the DRN hybrid model is efficient predictive model using the historical dataset for predicting the different level of autism.  ... 
doi:10.26483/ijarcs.v8i8.4604 fatcat:jkwivikjczcjbhmwmfql72pjba

A Comparative Study of Utilization of Single and Hybrid Data Mining Techniques in Heart Disease Diagnosis and Treatment Plan

Rajesh Jagtap
2015 International Journal of Computer Applications  
The current research aims to predict the possibility of getting heart disease according to dataset of patient's medical record .  ...  In Future,Additional data mining techniques can be incorporated to provide better results for better life of human being and the hybridization of data mining techniques will be useful in diagnosis and  ... 
doi:10.5120/ijca2015905556 fatcat:j6j62z5zc5ejzkyvj3waz3y2im

A Survey on Various Disease Prediction Techniques

C. Leancy Jannet, G. Sumalatha
2018 International Journal of Trend in Scientific Research and Development  
Using gene expression pattern we predict the disease outcome and implementation of pathway based approach for classifying disease based on hyper box principles, we also present a novel hybrid prediction  ...  An analysis of various diseases have been predicted using multiple data mining and text mining techniques. In this article we are going to discuss about 6 prediction techniques.  ...  Data mining in medical area is process of uncovering hidden patterns and information from huge medical datasets, examine and use them for disease prediction.  ... 
doi:10.31142/ijtsrd18624 fatcat:fkoh3fk3ljb7jgd6djk7gfylhq

Heart Disease Classification Based on Hybrid Ensemble Stacking Technique

Ahmed El Sheikh, Nader Mahmoud, Arabi Keshk
2021 IJCI. International Journal of Computers and Information  
Data mining techniques are usually used for finding anomalies, patterns and correlations within large data sets, thus it's crucial for clinical data analysis and various disease prediction.  ...  Heart diseases are considered one of the leading death rates for humanity in the recent decades. The early diagnosis and prediction of heart disease becomes a critical subject in medical domain.  ...  Recently, several authors study different data mining techniques for CD diagnosis and prediction.  ... 
doi:10.21608/ijci.2021.207732 fatcat:4nphn722efgkno2d5bqhji63ni

NeuroSVM: A Graphical User Interface for Identification of Liver Patients [article]

Kalyan Nagaraj, Amulyashree Sridhar
2015 arXiv   pre-print
The model resulted in a prediction accuracy of 98.83%. The results suggested that development of hybrid model improved the accuracy of prediction.  ...  In this context, this study utilizes data mining approaches for classification of liver patients from healthy individuals.  ...  Based on the review of literature, it was depicted that the past research studies have implemented different data mining techniques for classification of liver dataset.  ... 
arXiv:1502.05534v1 fatcat:xxbte5zrr5dcxegxmezh7fxu5u

Long Term Survival Prediction After Liver Transplantation using Cloud-based Hybrid Method

Nitin D. Thorve, D.Y.Patil School of Engineering
2020 International Journal of Engineering Research and  
Large volume of data about patients and their clinical information is present in medical databases For extracting the features and their connections from a tremendous database, different data mining methods  ...  Proposed an effective and accurate artificial neural network (ANN) model for the prediction of long-term survival of liver patients who undergo liver transplantation (LT) and then predicted data is uploaded  ...  The extraction of related attributes from a large data set requires data mining techniques. Extracting related attributes from a medical dataset requires careful attention.  ... 
doi:10.17577/ijertv9is060162 fatcat:t4cu3uajgfcpnjca7defpzej6y

A Comparative Analysis on Diabetes Datasets Using Data Mining Techniques

Dr. Hamid ur Rehman Zeenat Bashir
2021 Zenodo  
In past, many researchers have been worked on the early diagnosis of diabetes disease. They used different diabetes datasets for the prediction of diabetes disease.  ...  Diabetes disease is one of the chronic diseases and becoming a cause of death among peoples.  ...  Data mining (DM) is a process of analyzing and selecting hidden pattern for obtaining useful information. Data mining have different application in which one of them is medical diagnosis.  ... 
doi:10.5281/zenodo.5149790 fatcat:usyxbzcc2zc2vapnp3efh3pn3i

A Novel Method for Disease Prediction: Hybrid of Random Forest and Multivariate Adaptive Regression Splines

Dengju Yao, Jing Yang, Xiaojuan Zhan
2013 Journal of Computers  
Using data mining technology for disease prediction and diagnosis has become the focus of attention.  ...  Then, a novel hybrid method of random forest and multivariate adaptive regression splines is proposed for building disease prediction model.  ...  Thanks to UC Irvine Machine Learning Repository for providing the data. Thanks to Doctor Yang for helpful comments, suggestion and criticisms.  ... 
doi:10.4304/jcp.8.1.170-177 fatcat:kjvmbqc5jvhljcczlrhlkdyddm

Hybrid Privacy Preserving Mechanism: An Approach to ProtectHealth Care Data

M. Rameshkumar, V. Lakshmipraba
2018 Asian Journal of Computer Science and Technology  
A proficient strategy for cross breed information mining method is applied here which incorporates the combination of Navie Bayesian classifier and Homomorphic encryption calculation.  ...  Though lot of research has been carried out in these areas separately, a Hybrid architecture which combines both the features – efficiency and security is not widely found.  ...  Fig. 3 3 Encryption/decryption of user data Rate (TP): It corresponds to the number of positive examples that have been accurately predicted by the classification model. 4.  ... 
doi:10.51983/ajcst-2018.7.1.1826 fatcat:2qyef5sykbaktlwjegyvzj4eve

Comparison of Different Techniques to Predict Disease in Agriculture Production - A Review

Manpreet Kaur, Department of Computer Applications, Guru Kashi University, Talwandi Sabo, PB, India
2020 International Journal of Engineering Research and  
Analyzing the data can help in improving the quality of decision making and help the clinician's to monitor the high risk area and provide specialized treatments.  ...  With the increase in agricultural produce suffering from different types of disease, early detection and prediction of disease is the major area of concern.  ...  Comparison of three Data Mining models for Predicting Disease to Agriculture or Pre Disease to Agriculture by risk factors The Kaohsiun g journal of medical sciences, 2013 Logistic  ... 
doi:10.17577/ijertv9is080217 fatcat:qujmutkah5hgxpxumo7ay3pemm

Predictive data mining approaches in medical diagnosis: A review of some diseases prediction

Ramin Ghorbani, Rouzbeh Ghousi
2019 International Journal of Data and Network Science  
The study attempts to determine the most efficient data mining methods used for medical diagnosing purposes.  ...  All algorithms, data mining models, and evaluation methods are thoroughly reviewed with special consideration.  ...  The number of 168 articles associated with the implementation of data mining for medical diagnosis between 1997 and 2018 were identified.  ... 
doi:10.5267/j.ijdns.2019.1.003 fatcat:tzavawufrfcy3djjeo2dve63fm
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