Article
Engineering, Chemical
Waleed Ali, Faisal Saeed
Summary: Advancements in intelligent systems have greatly contributed to the fields of bioinformatics, health, and medicine. This paper proposes a hybrid filter-genetic feature selection approach to improve the performance of cancer classification by addressing the high-dimensionality and noisy nature of microarray data. Experimental results demonstrate that the proposed method outperforms common machine learning methods in terms of Accuracy, Recall, Precision, and F-measure.
Article
Biology
Shyam Marjit, Trinav Bhattacharyya, Bitanu Chatterjee, Ram Sarkar
Summary: This paper proposes a meta-heuristic approach called SAGA, which combines simulated annealing and genetic algorithm to identify informative genes from high-dimensional datasets. SAGA outperforms other algorithms by utilizing a clustering-based population generation and a score-based filter approach.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Motahare Akhavan, Seyed Mohammad Hossein Hasheminejad
Summary: A new two-phase gene selection method for microarray data is proposed in this study. This method reduces the number of genes significantly and improves the classification accuracy through anomaly detection and guided genetic algorithm.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Xiongshi Deng, Min Li, Shaobo Deng, Lei Wang
Summary: This paper proposes a two-stage gene selection method combining XGBoost and XGBoost-MOGA for cancer classification in microarray datasets. The experimental results show that this method outperforms other state-of-the-art algorithms in terms of accuracy, F-score, precision, and recall.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2022)
Article
Biochemical Research Methods
Kun Yu, Weidong Xie, Linjie Wang, Wei Li
Summary: The proposed feature selection algorithm in the study outperformed other methods in microarray data analysis, showing higher stability and classification accuracy. The selected biomarkers also matched the clinical data provided by the cooperative hospital.
BMC BIOINFORMATICS
(2021)
Article
Automation & Control Systems
Weidong Xie, Yushan Fang, Kun Yu, Xin Min, Wei Li
Summary: MFRAG is a new hybrid feature selection method that mimics the natural principle of survival of the fittest by enhancing the stability and reliability of the selection process through fusion mechanisms and integrated models, and guides the evolutionary process through a set of lists generated by a feature fusion model.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Serhat Kilicarslan, Emrah Donmez
Summary: This study introduces a novel approach combining adaptive particle swarm optimization and artificial bee colony algorithm to effectively classify microarray datasets for early diagnosis of cancer. The most defining features are selected through feature selection algorithms, and different classification algorithms are used for classification.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Laith Abualigah, Akram Jamal Dulaimi
Summary: The SCAGA method combines the SCA and GA algorithms, demonstrating better performance in balancing the exploitation and exploration strategies of the search space.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Mohammad Ahmadi Ganjei, Reza Boostani
Summary: In this paper, a new hybrid feature selection approach that combines filter and wrapper methods is proposed. By ranking, clustering, and searching the features, this method achieves better performance on high-dimensional datasets.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Information Systems
Hasna Chamlal, Tayeb Ouaderhman, Fatima Ezzahra Rebbah
Summary: The feature selection process is crucial in various fields, especially in bioinformatics and microarray gene expression data analysis. This study introduces a new feature selection method that can handle high-dimensional data and effectively select features in large-scale gene datasets.
INFORMATION SCIENCES
(2022)
Article
Mathematics, Interdisciplinary Applications
Dong Yang, Peijian Wu
Summary: This paper explores the optimization of e-commerce logistics and distribution networks, proposing solutions that take into account city traffic conditions and establishing an optimization model through various methods. The study focuses on vehicle path problems, multidimensional impact maximization problems, and proposes solutions for emergency material delivery path planning.
Review
Multidisciplinary Sciences
Nursabillilah Mohd Ali, Rosli Besar, Nor Azlina Ab Aziz
Summary: Breast cancer is the most dominant cancer among women worldwide. Gene expression microarray is employed for accurate classification and prognosis, but suffers from limitations such as large number of features, limited sample size, and irrelevant features, making it difficult to determine the actual features contributing to cancer classification. Therefore, feature selection methods are needed to identify relevant and discriminant feature subsets.
Article
Biochemical Research Methods
Wei Li, Yuhuan Chi, Kun Yu, Weidong Xie
Summary: This paper proposes a two-stage hybrid biomarker selection method based on ensemble filter and binary differential evolution incorporating binary African vultures optimization (EF-BDBA), which can effectively reduce the dimension of microarray data and obtain optimal biomarkers. Compared with traditional feature selection methods and advanced hybrid methods, the proposed method achieves higher classification accuracy and identifies excellent biomarkers while retaining fewer features.
BMC BIOINFORMATICS
(2023)
Article
Computer Science, Information Systems
Yu Zhou, Wenjun Zha, Junhao Kang, Xiao Zhang, Xu Wang
Summary: This paper proposes a problem-specific non-dominated sorting genetic algorithm (PS-NSGA) that can minimize three objectives of feature selection. By applying an accuracy-preferred domination operator and a quick bit mutation, the algorithm converges faster and better, achieving competitive classification accuracy in experiments.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Hardware & Architecture
Nilesh Kunhare, Ritu Tiwari, Joydip Dhar
Summary: An intrusion detection system is crucial for detecting threats and unauthorized access. This paper proposes a novel feature selection method using a genetic algorithm and hybrid classification with logistic regression and decision tree. Experimental results show that the gray wolf optimization algorithm achieves the best performance with a reduced feature set. The proposed method is compared with existing methods, demonstrating improved performance.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Deepa Kanmani Swaminathan, E. Kirubakaran, Elijah Blessing Rajsingh, A. Shamila Ebenezer
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2019)
Article
Computer Science, Information Systems
R. Indhumathi, S. Sathiya Devi
Summary: Deep learning is widely used in the medical field to improve privacy of original medical data through synthetic data generation and prevent attacks. The Healthcare Cramer Generative Adversarial Network (HCGAN) method effectively prevents attacks and generates synthetic data with high privacy.
DISTRIBUTED AND PARALLEL DATABASES
(2022)
Article
Engineering, Mechanical
S. Alagarsamy, R. Balasundaram, M. Ravichandran, V Mohanavel, Alagar Karthick, S. Sathiya Devi
Summary: This study applied a data-driven approach using decision tree algorithm to analyze the wear rate of ZnO-filled AA7075 composites, confirming reinforcement as the primary factor affecting wear. Optimal experimental parameters were determined through Taguchi analysis, validating the effectiveness of the DT algorithm.
SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES
(2021)
Article
Computer Science, Cybernetics
Govindarajan Parthasarathy, Shanmugam Sathiya Devi
Summary: A Recommendation System (RS) helps users choose their desired targets from a large amount of online information. The existing content-based and collaborative filtering systems have limitations, so this article proposes a new hybrid recommender system to optimize the recommendation list for users.
CYBERNETICS AND SYSTEMS
(2023)
Article
Public, Environmental & Occupational Health
B. L. Radhakrishnan, E. Kirubakaran, Immanuel Johnraja Jebadurai, A. Immanuel Selvakumar, J. Dinesh Peter
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Public, Environmental & Occupational Health
Shilpa Shyam, Sujitha Juliet, Kirubakaran Ezra
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Engineering, Biomedical
S. Vidivelli, S. Sathiya Devi
Summary: Breast cancer is the deadliest disease among women and mammography is the main method for detection. However, early detection using mammography remains complex. This study proposes a system that includes pre-processing, segmentation, feature extraction, optimal feature selection, and classification. An optimized ensemble classifier is used for prediction, and the weights of the CNN are fine-tuned using Self Improved Cat Swarm Optimization (SI-CSO) algorithm.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Automation & Control Systems
R. Rajakumar, S. Sathiya Devi
Summary: With advancements in information technologies, the production of vast amounts of data from social media, smartphones, and sensor devices has become a significant challenge. This study develops a technique called ODFST-SDC that combines outlier detection with feature selection for streaming data classification. The technique utilizes categorical encoding, null value removal, Local Correlation Integral (LOCI) for outlier detection, red deer algorithm (RDA) for feature selection, and kernel extreme learning machine (KELM) classifier. Experimental results demonstrate the effectiveness of the ODFST-SDC technique over recent approaches.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
R. Indhumathi, S. Sathiya Devi
Summary: Remote health data monitoring has gained attention with the increased implementation of the Internet of Things (IoT). However, due to limitations of IoT devices, users' health data are stored in centralized third-party systems, leading to privacy issues. This study proposes a medical data transmission and preservation strategy based on a hospital's private blockchain, including data sanitization, optimal key generation, and data restoration.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
S. Sathiya Devi, R. Indhumathi
Summary: The fast advancement of information technology has led to more efficient information storage and retrieval. However, incorrect data exchange can lead to privacy breaches. This paper proposes a method called Quasi Identification Based on Tree (QIBT) for automatically identifying Quasi Identifiers (QIs). The method uses a tree data structure to derive unique and infrequent attribute values from the dataset, yielding superior results compared to other approaches.
Article
Computer Science, Information Systems
G. Parthasarathy, S. Sathiya Devi
Summary: This paper proposes a model-based collaborative filtering recommender system to address the sparsity and scalability problems. By utilizing ensemble learning and enhanced clustering algorithm, the proposed model achieves superior performance in movie recommendations on the Movielens dataset.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Computer Science, Information Systems
S. Sathiya Devi, S. Vidivelli
Summary: This research proposes a method for characterizing the shape and gray-scale complexity of breast cancer in image processing, and extracts fractal features using the Modified Differential Box Counting (MDBC) algorithm. The MDBC method overcomes the limitations of traditional methods in handling tumor regions with the same roughness but different gray levels. The proposed method outperforms automatic detection and classification and achieves improved accuracy of 93% compared to existing feature methods.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Information Science & Library Science
Beulah Christalin Latha Christudas, E. Kirubakaran, P. Ranjit Jeba Thangaiah
TELEMATICS AND INFORMATICS
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
S. Vidivelli, S. Sathiya Devi
COMPUTATIONAL INTELLIGENCE, CYBER SECURITY AND COMPUTATIONAL MODELS, ICC3 2015
(2016)
