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Multiclass feature selection with metaheuristic optimization algorithms: a review
Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …
selection is harder to perform since most classifications are binary. The feature selection …
DeepCC: a novel deep learning-based framework for cancer molecular subtype classification
Molecular subty** of cancer is a critical step towards more individualized therapy and
provides important biological insights into cancer heterogeneity. Although gene expression …
provides important biological insights into cancer heterogeneity. Although gene expression …
Medical Internet of things using machine learning algorithms for lung cancer detection
This paper empirically evaluates the several machine learning algorithms adaptable for lung
cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for …
cancer detection linked with IoT devices. In this work, a review of nearly 65 papers for …
[HTML][HTML] Prediction of cancer disease using machine learning approach
FJ Shaikh, DS Rao - Materials Today: Proceedings, 2022 - Elsevier
Cancer has identified a diverse condition of several various subtypes. The timely screening
and course of treatment of a cancer form is now a requirement in early cancer research …
and course of treatment of a cancer form is now a requirement in early cancer research …
A deep learning-based approach for detection of lung cancer using self adaptive sea lion optimization algorithm (SA-SLnO)
The main intent of this paper is to design and implement a novel methodology for lung
cancer prediction using the patient's health record. Feature extraction is performed using two …
cancer prediction using the patient's health record. Feature extraction is performed using two …
Lung cancer prediction from microarray data by gene expression programming
H Azzawi, J Hou, Y **ang, R Alanni - IET systems biology, 2016 - Wiley Online Library
Lung cancer is a leading cause of cancer‐related death worldwide. The early diagnosis of
cancer has demonstrated to be greatly helpful for curing the disease effectively. Microarray …
cancer has demonstrated to be greatly helpful for curing the disease effectively. Microarray …
Enhanced lung cancer classification and prediction based on hybrid neural network approach
Cancer is the leading killer on a global scale. As the leading cause of cancer-related
mortality, lung cancer is among the most prevalent forms of the disease. Uncontrolled cell …
mortality, lung cancer is among the most prevalent forms of the disease. Uncontrolled cell …
Posterior probability based ensemble strategy using optimizing decision directed acyclic graph for multi-class classification
L Zhou, H Fujita - Information Sciences, 2017 - Elsevier
Ensemble strategy is important to develop a decomposition and ensemble method for multi-
class classification problems. Most existing ensemble strategies use predetermined and …
class classification problems. Most existing ensemble strategies use predetermined and …
Exploring the effectiveness of dynamic ensemble selection in the one-versus-one scheme
Abstract The One-versus-One (OVO) strategy is one of the most common and effective
techniques to deal with multi-class classification problems. The basic idea of an OVO …
techniques to deal with multi-class classification problems. The basic idea of an OVO …
Iterative ensemble feature selection for multiclass classification of imbalanced microarray data
Background Microarray technology allows biologists to monitor expression levels of
thousands of genes among various tumor tissues. Identifying relevant genes for sample …
thousands of genes among various tumor tissues. Identifying relevant genes for sample …