Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing

被引：0

作者：

Chakraborty, Pritam ^{[1
]}

Bandyopadhyay, Anjan ^{[1
]}

Sahu, Preeti Padma ^{[1
]}

Burman, Aniket ^{[1
]}

Mallik, Saurav ^{[2
]}

Alsubaie, Najah ^{[3
]}

Abbas, Mohamed ^{[4
]}

Alqahtani, Mohammed S. ^{[5
,6
]}

Soufiene, Ben Othman ^{[7
]}

机构：

[1] School of computer engineering, KIIT University, Patia, Odisha, Bhubaneswar,751024, India

[2] Department of Environmental Health, Harvard T H Chan School of public Health, 677 Harrington Avenue, Boston,MA,02115, United States

[3] Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh,11671, Saudi Arabia

[4] Electrical Engineering Department, College of Engineering, King Khalid University, Abha,61421, Saudi Arabia

[5] Radiological Sciences Department, College of Applied Medical Sciences, King Khalid University, Abha,61421, Saudi Arabia

[6] BioImaging Unit, Space Research Centre, University of Leicester, Michael Atiyah Building, Leicester,LE1 7RH, United Kingdom

[7] PRINCE Laboratory Research, ISITcom, Hammam Sousse, University of Sousse, Sousse, Tunisia

来源：

BMC Bioinformatics | / 25卷 / 01期

关键词：

D O I：

10.1186/s12859-024-05866-8

中图分类号：

学科分类号：

摘要：

引用

共 50 条

[1] Data preprocessing and feature selection techniques in gait recognition: A comparative study of machine learning and deep learning approaches
Parashar, Anubha
Parashar, Apoorva
Ding, Weiping
Shabaz, Mohammad
Rida, Imad
[J]. PATTERN RECOGNITION LETTERS, 2023, 172 : 65 - 73
[2] Data Cleansing Meets Feature Selection: A Supervised Machine Learning Approach
Tallon-Ballesteros, Antonio J.
Riquelme, Jose C.
[J]. BIOINSPIRED COMPUTATION IN ARTIFICIAL SYSTEMS, PT II, 2015, 9108 : 369 - 378
[3] Data Classification Using Feature Selection And kNN Machine Learning Approach
Begum, Shemim
Chakraborty, Debasis
Sarkar, Ram
[J]. 2015 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (CICN), 2015, : 811 - 814
[4] Feature Selection of Photoplethysmograph Data in Machine Learning
Haq, Faris Atoil
Sarno, Riyanarto
Abdillah, Rifqi
Amri, Taufiq Choirul
Septiyanto, Abdullah Faqih
Sungkono, Kelly Rossa
[J]. 2023 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION, ICAIIC, 2023, : 315 - 320
[5] Impacts of Feature Selection on Predicting Machine Failures by Machine Learning Algorithms
Bezerra, Francisco Elanio
de Oliveira Neto, Geraldo Cardoso
Cervi, Gabriel Magalhaes
Mazetto, Rafaella Francesconi
de Faria, Aline Mariane
Vido, Marcos
Lima, Gustavo Araujo
de Araujo, Sidnei Alves
Sampaio, Mauro
Amorim, Marlene
[J]. APPLIED SCIENCES-BASEL, 2024, 14 (08):
[6] A Scalable Feature Selection and Model Updating Approach for Big Data Machine Learning
Yang, Baijian
Zhang, Tonglin
[J]. 2016 IEEE INTERNATIONAL CONFERENCE ON SMART CLOUD (SMARTCLOUD), 2016, : 146 - 151
[7] An efficient feature subset selection approach for machine learning
Rincy, N. Thomas
Gupta, Roopam
[J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (08) : 12737 - 12830
[8] An efficient feature subset selection approach for machine learning
Thomas Rincy N
Roopam Gupta
[J]. Multimedia Tools and Applications, 2021, 80 : 12737 - 12830
[9] Quantum Optimization Approach for Feature Selection in Machine Learning
Fleury, Gerard
Vulpescu, Bogdan
Lacomme, Philippe
[J]. METAHEURISTICS, MIC 2024, PT I, 2024, 14753 : 281 - 288
[10] An Explainable Feature Selection Approach for Fair Machine Learning
Yang, Zhi
Wang, Ziming
Huang, Changwu
Yao, Xin
[J]. ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2023, PT VIII, 2023, 14261 : 75 - 86

← 1 2 3 4 5 →