Machine learning in medical applications: A review of state-of-the-art methods

M Shehab, L Abualigah, Q Shambour… - Computers in Biology …, 2022 - Elsevier
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

[HTML][HTML] Classification of breast cancer using microarray gene expression data: A survey

M Abd-Elnaby, M Alfonse, M Roushdy - Journal of Biomedical Informatics, 2021 - Elsevier
Cancer, in particular breast cancer, is considered one of the most common causes of death
worldwide according to the world health organization. For this reason, extensive research …

[HTML][HTML] Survey on machine learning and deep learning applications in breast cancer diagnosis

G Chugh, S Kumar, N Singh - Cognitive Computation, 2021 - Springer
Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …

Comparison of machine learning methods for breast cancer diagnosis

EA Bayrak, P Kırcı, T Ensari - 2019 Scientific meeting on …, 2019 - ieeexplore.ieee.org
Cancer is the common problem for all people in the world with all types. Particularly, Breast
Cancer is the most frequent disease as a cancer type for women. Therefore, any …

Application of nature inspired soft computing techniques for gene selection: a novel frame work for classification of cancer

RM Aziz - Soft Computing, 2022 - Springer
Abstract A modified Artificial Bee Colony (ABC) metaheuristics optimization technique is
applied for cancer classification, that reduces the classifier's prediction errors and allows for …

[PDF][PDF] Breast cancer data classification using ensemble machine learning.

MA Jabbar - Engineering & Applied Science Research, 2021 - thaiscience.info
Breast cancer (BC) is the largest cause of death in women. Accurate classification of breast
cancer data is important in cancer diagnosis and classification of Malignant and Benign …

A survey of machine learning approaches applied to gene expression analysis for cancer prediction

M Khalsan, LR Machado, ES Al-Shamery, S Ajit… - IEEE …, 2022 - ieeexplore.ieee.org
Machine learning approaches are powerful techniques commonly employed for developing
cancer prediction models using associated gene expression and mutation data. This …

Feature selection and its use in big data: challenges, methods, and trends

M Rong, D Gong, X Gao - Ieee Access, 2019 - ieeexplore.ieee.org
Feature selection has been an important research area in data mining, which chooses a
subset of relevant features for use in the model building. This paper aims to provide an …

An Efficient Cancer Classification Model Using Microarray and High‐Dimensional Data

H Fathi, H AlSalman, A Gumaei… - Computational …, 2021 - Wiley Online Library
Cancer can be considered as one of the leading causes of death widely. One of the most
effective tools to be able to handle cancer diagnosis, prognosis, and treatment is by using …

Breast cancer prediction from microRNA profiling using random subspace ensemble of LDA classifiers via Bayesian optimization

SK Sharma, K Vijayakumar, VJ Kadam… - Multimedia Tools and …, 2022 - Springer
Breast cancer rates are rising. It also remains the second principal reason for cancer-related
mortality in females, and the mortality rate is also drastically rising. In recent years …