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Enhanced feature selection and ensemble learning for cardiovascular disease prediction: hybrid GOL2-2 T and adaptive boosted decision fusion with babysitting refinement.

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第一作者： S Phani,Praveen

第一单位： Department of Computer Science and Engineering, Prasad V Potluri Siddhartha Institute of Technology, Vijayawada, India.

作者： S Phani,Praveen ^[1] ; Mohammad Kamrul,Hasan ^[2] ; Siti Norul Huda Sheikh,Abdullah ^[2] ; Uddagiri,Sirisha ^[1] ; N S Koti Mani Kumar,Tirumanadham ^[3] ; Shayla,Islam ^[4] ; Fatima Rayan Awad,Ahmed ^[5] ; Thowiba E,Ahmed ^[6] ; Ayman Afrin,Noboni ^[7] ; Gabriel Avelino,Sampedro ^[8] ; Chan Yeob,Yeun ^[9] ; Taher M,Ghazal ^[2]

作者单位： Department of Computer Science and Engineering, Prasad V Potluri Siddhartha Institute of Technology, Vijayawada, India. ^[1] Faculty of Information Science and Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia. ^[2] Department of Computer Science and Engineering, Sir C R Reddy College of Engineering, Eluru, India. ^[3] Institute of Computer Science and Digital innovation, UCSI University, Kuala Lumpur, Malaysia. ^[4] Computer Science Department, College of Computer Engineering and Science, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia. ^[5] Computer Science Department, College of Science and Humanities-Jubail, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia. ^[6] Department of Surgery, Medical College For Women and Hospital, Dhaka, Bangladesh. ^[7] Faculty of Information and Communication Studies, University of the Philippines Open University, Los Baños, Philippines.;Center for Computational Imaging and Visual Innovations, De La Salle University, Manila, Philippines. ^[8] Centre for Cyber Physical Systems, Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates. ^[9]

关键词 adaboost decision fusion (ABDF)adaptive boosted decision fusion cardiovascular disease interquartile range multivariate imputation by chained equations synthetic minority over-sampling technique

DOI 10.3389/fmed.2024.1407376

PMID 39071085

发布时间 2024-07-30

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Enhanced feature selection and ensemble learning for cardiovascular disease prediction: hybrid GOL2-2 T and adaptive boosted decision fusion with babysitting refinement.

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Enhanced feature selection and ensemble learning for cardiovascular disease prediction: hybrid GOL2-2 T and adaptive boosted decision fusion with babysitting refinement.

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