Selecting critical features for data classification based on machine learning methods

RC Chen, C Dewi, SW Huang, RE Caraka - Journal of Big Data, 2020 - Springer
Feature selection becomes prominent, especially in the data sets with many variables and
features. It will eliminate unimportant variables and improve the accuracy as well as the …

Identification of significant features and data mining techniques in predicting heart disease

MS Amin, YK Chiam, KD Varathan - Telematics and Informatics, 2019 - Elsevier
Cardiovascular disease is one of the biggest cause for morbidity and mortality among the
population of the world. Prediction of cardiovascular disease is regarded as one of the most …

[PDF][PDF] Heart disease prediction using machine learning techniques: a survey

VV Ramalingam, A Dandapath… - International Journal of …, 2018 - researchgate.net
Heart related diseases or Cardiovascular Diseases (CVDs) are the main reason for a huge
number of death in the world over the last few decades and has emerged as the most life …

A Decisive Metaheuristic Attribute Selector Enabled Combined Unsupervised‐Supervised Model for Chronic Disease Risk Assessment

S Mishra, HK Thakkar, P Singh… - Computational …, 2022 - Wiley Online Library
Advanced predictive analytics coupled with an effective attribute selection method plays a
pivotal role in the precise assessment of chronic disorder risks in patients. Traditional …

Exploring feature selection and classification methods for predicting heart disease

R Spencer, F Thabtah, N Abdelhamid… - Digital …, 2020 - journals.sagepub.com
Machine learning has been used successfully to improve the accuracy of computer-aided
diagnosis systems. This paper experimentally assesses the performance of models derived …

Performance evaluation of a proposed machine learning model for chronic disease datasets using an integrated attribute evaluator and an improved decision tree …

S Mishra, PK Mallick, HK Tripathy, AK Bhoi… - Applied Sciences, 2020 - mdpi.com
There is a consistent rise in chronic diseases worldwide. These diseases decrease immunity
and the quality of daily life. The treatment of these disorders is a challenging task for medical …

A hybrid method for heart disease diagnosis utilizing feature selection based ensemble classifier model generation

J Abdollahi, B Nouri-Moghaddam - Iran Journal of Computer Science, 2022 - Springer
Heart disease is one of the most complicated diseases, and it affects a large number of
individuals throughout the world. In healthcare, particularly cardiology, early and accurate …

Cervical cancer diagnosis using random forest classifier with SMOTE and feature reduction techniques

SF Abdoh, MA Rizka, FA Maghraby - IEEE Access, 2018 - ieeexplore.ieee.org
Cervical cancer is the fourth most common malignant disease in women's worldwide. In
most cases, cervical cancer symptoms are not noticeable at its early stages. There are a lot …

Applications of machine learning techniques to predict diagnostic breast cancer

V Chaurasia, S Pal - SN Computer Science, 2020 - Springer
This article compares six machine learning (ML) algorithms: Classification and Regression
Tree (CART), Support Vector Machine (SVM), Naïve Bayes (NB), K-Nearest Neighbors …

Cervical cancer identification with synthetic minority oversampling technique and PCA analysis using random forest classifier

R Geetha, S Sivasubramanian, M Kaliappan… - Journal of medical …, 2019 - Springer
Cervical cancer is the fourth most communal malignant disease amongst women worldwide.
In maximum circumstances, cervical cancer indications are not perceptible at its initial …