Reviewing ensemble classification methods in breast cancer
Context Ensemble methods consist of combining more than one single technique to solve
the same task. This approach was designed to overcome the weaknesses of single …
the same task. This approach was designed to overcome the weaknesses of single …
[HTML][HTML] Prediction of breast cancer using machine learning approaches
Background: Breast cancer is considered one of the most common cancers in women
caused by various clinical, lifestyle, social, and economic factors. Machine learning has the …
caused by various clinical, lifestyle, social, and economic factors. Machine learning has the …
Breast tumor classification using an ensemble machine learning method
Breast cancer is the most common cause of death for women worldwide. Thus, the ability of
artificial intelligence systems to detect possible breast cancer is very important. In this paper …
artificial intelligence systems to detect possible breast cancer is very important. In this paper …
Optimized stacking ensemble learning model for breast cancer detection and classification using machine learning
Breast cancer is the most frequently encountered medical hazard for women in their forties,
affecting one in every eight women. It is the greatest cause of death worldwide, and early …
affecting one in every eight women. It is the greatest cause of death worldwide, and early …
Classification techniques in breast cancer diagnosis: a systematic literature review
Data mining (DM) consists in analysing a set of observations to find unsuspected
relationships and then summarising the data in new ways that are both understandable and …
relationships and then summarising the data in new ways that are both understandable and …
CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer
This paper presents a new data mining technique for an accurate prediction of breast cancer
(BC), which is one of the major mortality causes among women around the globe. The main …
(BC), which is one of the major mortality causes among women around the globe. The main …
A case-based ensemble learning system for explainable breast cancer recurrence prediction
Significant progress has been achieved in recent years in the application of artificial
intelligence (AI) for medical decision support. However, many AI-based systems often only …
intelligence (AI) for medical decision support. However, many AI-based systems often only …
Efficient feature selection and ML algorithm for accurate diagnostics
Abstract Machine learning algorithms have been deployed in numerous optimization,
prediction and classification problems. This has endeared them for application in fields such …
prediction and classification problems. This has endeared them for application in fields such …
Predicting breast cancer biopsy outcomes from BI-RADS findings using random forests with chi-square and MI features
To look for early breast cancer signs and indications, mammography screening is one of the
best approaches available. Screening mammograms are the most commonly recognized …
best approaches available. Screening mammograms are the most commonly recognized …
[Retracted] Breast Tumor Detection Using Robust and Efficient Machine Learning and Convolutional Neural Network Approaches
MM Khan, T Tazin, M Zunaid Hussain… - Computational …, 2022 - Wiley Online Library
Breast cancer develops when cells in the breast expand and divide uncontrollably, resulting
in a lump of tissue known as a tumor. This lump of tissue is called a tumor. After skin cancer …
in a lump of tissue known as a tumor. This lump of tissue is called a tumor. After skin cancer …