A Comprehensive Review on Heart Disease Risk Prediction using Machine Learning and Deep Learning Algorithms
Cardiovascular diseases claim approximately 17.9 million lives annually, with heart attacks
and strokes accounting for over 80% of these deaths. Key risk factors, including …
and strokes accounting for over 80% of these deaths. Key risk factors, including …
Novel Feature Reduction (NFR) model with machine learning and data mining algorithms for effective disease risk prediction
SJ Pasha, ES Mohamed - Ieee Access, 2020 - ieeexplore.ieee.org
Presently, the application of machine learning (ML) and data mining (DM) techniques have a
vital role in healthcare systems and wisely convert all obtainable data into beneficial …
vital role in healthcare systems and wisely convert all obtainable data into beneficial …
A cnn approach for corn leaves disease detection to support digital agricultural system
Correct, fast and early detection of corn leave diseases and their prevention and control at
the earlier stages is profitable. To improve the detection accuracy of corn leaf diseases, a …
the earlier stages is profitable. To improve the detection accuracy of corn leaf diseases, a …
Enhancing software fault prediction through feature selection with spider wasp optimization algorithm
Software fault prediction (SFP) is a critical focus in software engineering, aiming to enhance
productivity and minimize costs by detecting faults early. Feature selection (FS) is pivotal in …
productivity and minimize costs by detecting faults early. Feature selection (FS) is pivotal in …
[HTML][HTML] A Jaya algorithm based wrapper method for optimal feature selection in supervised classification
In recent years, Jaya optimization algorithm has been successfully applied in several
optimization problems. This paper presents a novel feature selection (FS) approach based …
optimization problems. This paper presents a novel feature selection (FS) approach based …
Feature selection using golden jackal optimization for software fault prediction
A program's bug, fault, or mistake that results in unintended results is known as a software
defect or fault. Software flaws are programming errors due to mistakes in the requirements …
defect or fault. Software flaws are programming errors due to mistakes in the requirements …
A hybrid approach of spotted hyena optimization integrated with quadratic approximation for training wavelet neural network
Spotted hyena optimization (SHO) is one of the newly evolved swarm-based metaheuristic
optimization methods based on the social life cycle of hyenas. In recent times SHO is being …
optimization methods based on the social life cycle of hyenas. In recent times SHO is being …
Multi-layer perceptron classification method of medical data based on biogeography-based optimization algorithm with probability distributions
XD Li, JS Wang, WK Hao, M Wang, M Zhang - Applied Soft Computing, 2022 - Elsevier
In the field of medical informatics, the accuracy of medical data classification plays a vital
role. Multi-layer Perceptron (MLP), as one of the most widely used neural networks, has …
role. Multi-layer Perceptron (MLP), as one of the most widely used neural networks, has …
Optimal selection of features using artificial electric field algorithm for classification
The high-dimensional features in the data may affect the performance of the classification
model as all of them are not useful. The selection of relevant optimal features is a tedious …
model as all of them are not useful. The selection of relevant optimal features is a tedious …
LAGOA: Learning automata based grasshopper optimization algorithm for feature selection in disease datasets
In predictive modelling it is important to use any feature selection methods as irrelevant
features when used with powerful classifiers can lead to over-fitting and thus create models …
features when used with powerful classifiers can lead to over-fitting and thus create models …