A systematic review on metaheuristic optimization techniques for feature selections in disease diagnosis: open issues and challenges
There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Cancer detection and segmentation using machine learning and deep learning techniques: A review
HM Rai - Multimedia Tools and Applications, 2024 - Springer
Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …
to other type's human diseases. The most common and dangerous types of cancers are lung …
[HTML][HTML] Predicting breast cancer from risk factors using SVM and extra-trees-based feature selection method
Develo** a prediction model from risk factors can provide an efficient method to recognize
breast cancer. Machine learning (ML) algorithms have been applied to increase the …
breast cancer. Machine learning (ML) algorithms have been applied to increase the …
Feature wise normalization: An effective way of normalizing data
This paper presents a novel Feature Wise Normalization approach for the effective
normalization of data. In this approach, each feature is normalized independently with one of …
normalization of data. In this approach, each feature is normalized independently with one of …
Artificial intelligence based medical decision support system for early and accurate breast cancer prediction
Feature selection, which picks the optimal subset of characteristics related to the target data
by deleting unnecessary data, is one of the most important aspects of the machine learning …
by deleting unnecessary data, is one of the most important aspects of the machine learning …
[HTML][HTML] A novel approach for data feature weighting using correlation coefficients and min–max normalization
In the realm of data analysis and machine learning, achieving an optimal balance of feature
importance, known as feature weighting, plays a pivotal role, especially when considering …
importance, known as feature weighting, plays a pivotal role, especially when considering …
Breast cancer prediction using a hybrid method based on butterfly optimization algorithm and ant lion optimizer
The design and development of a computer-based system for breast cancer detection are
largely reliant on feature selection techniques. These techniques are used to reduce the …
largely reliant on feature selection techniques. These techniques are used to reduce the …
[HTML][HTML] A breast cancer risk predication and classification model with ensemble learning and big data fusion
Breast cancer is a major health issue for women all over the world. Effective care and better
patient outcomes depend on early identification and precise risk prediction. Ensemble …
patient outcomes depend on early identification and precise risk prediction. Ensemble …
Computer-aided detection of breast cancer on the Wisconsin dataset: An artificial neural networks approach
The early detection of breast cancer (BC) has a significant impact on reducing the disease's
mortality rate. As an effective cost-and time-saving tool, computer-aided diagnosis (CAD) …
mortality rate. As an effective cost-and time-saving tool, computer-aided diagnosis (CAD) …
GARL-Net: graph based adaptive regularized learning deep network for breast cancer classification
Across the globe, women suffer from breast cancer fatal disease. It is arising surprisingly due
to a lack of awareness among them and the inconvenient reach of diagnostic systems. Many …
to a lack of awareness among them and the inconvenient reach of diagnostic systems. Many …