Effective Disease Prediction on Gene Family Abundance Using Feature Selection and Binning Approach

2020 ◽  
pp. 19-28
Author(s):  
Thanh-Hai Nguyen ◽  
Tan-Tai Phan ◽  
Cong-Tinh Dao ◽  
Dang-Vinh-Phuc Ta ◽  
Thi-Ngoc-Cham Nguyen ◽  
...  
Keyword(s):  
Feature Selection ◽  
Gene Family ◽  
Disease Prediction

scholarly journals Diabetes disease prediction using decision tree for feature selection

2021 ◽  
Vol 1964 (6) ◽  
pp. 062116
Author(s):  
Jayakumar Sadhasivam ◽  
V Muthukumaran ◽  
J Thimmia Raja ◽  
Rose Bindu Joseph ◽  
Meram Munirathanam ◽  
...  
Keyword(s):  
Feature Selection ◽  
Decision Tree ◽  
Disease Prediction

scholarly journals Classification models for heart disease prediction using feature selection and PCA

2020 ◽  
Vol 19 ◽  
pp. 100330 ◽  
Author(s):  
Anna Karen Gárate-Escamila ◽  
Amir Hajjam El Hassani ◽  
Emmanuel Andrès
Keyword(s):  
Feature Selection ◽  
Heart Disease ◽  
Disease Prediction ◽  
Classification Models

scholarly journals Heart disease prediction using SVM based neuro-fuzzy technique in the cloud computing

2018 ◽  
Vol 7 (2.20) ◽  
pp. 153
Author(s):  
Dr M. Sadish Sendil
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Feature Selection ◽  
Heart Disease ◽  
Disease Diagnosis ◽  
Disease Prediction ◽  
Specific Level ◽  
Huge Data ◽  
Neuro Fuzzy ◽  
Heart Disease Diagnosis

Cloud computing is a technique for conveying on information development benefits in resources are recovered from the Internet through online based device and applications, as opposed to a speedy association with a server. Cloud has numerous applications in the meadows of education, social networking, and medicine. But the benefit of the cloud for medical reasons is seamless, specifically an account of the huge data generated by the healthcare industry. Heart disease diagnosis determination strategy is essential and significant issue for the patient's wellbeing. Furthermore, it will help to decrease infection to a more specific level. Computer-aided decision support method performs a vital task in medical line. Data mining gives the system and innovation to change these heaps of data into effective information for decision-making. When applying data mining techniques it carries shorter time for the prediction of the disease with more exactness. The hybrid work of preprocessing, feature selection using SVM and SVM based Neuro-Fuzzy data mining strategies utilizing as a part of the determination of the heart disease is incredibly impressive. The framework is to build up a technique for arranging for heart level of the patient relies upon highlight information utilizing Neuro-Fuzzy surmising system. The experiment is done with two different analysis that is one with preprocessed data alone and applied SVM based Neuro Fuzzy Technique and the second one is accomplished with feature selection done data and applied SVM based Neuro Fuzzy Technique. The results prove that the system result of the first one gives 92% accuracy in the heart disease prediction. The second one is giving 95.11% accuracy in the heart disease prediction.  

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