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Classification and Prediction Model using Hybrid Technique for Medical Datasets
2015
International Journal of Computer Applications
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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
2020
JOIV: International Journal on Informatics Visualization
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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
2015
Indian Journal of Science and Technology
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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
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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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
DRN HYBRID MODEL FOR PREDICTING AUTISM USING RAPID MINER TOOL
2017
International Journal of Advanced Research in Computer Science
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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
2015
International Journal of Computer Applications
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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
2018
International Journal of Trend in Scientific Research and Development
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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
2021
IJCI. International Journal of Computers and Information
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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]
2015
arXiv
pre-print
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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
2020
International Journal of Engineering Research and
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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
2021
Zenodo
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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
2013
Journal of Computers
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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
2018
Asian Journal of Computer Science and Technology
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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
2020
International Journal of Engineering Research and
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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
2019
International Journal of Data and Network Science
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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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