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

Autor: Praveen SP; Department of Computer Science and Engineering, Prasad V Potluri Siddhartha Institute of Technology, Vijayawada, India., Hasan MK; Faculty of Information Science and Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia., Abdullah SNHS; Faculty of Information Science and Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia., Sirisha U; Department of Computer Science and Engineering, Prasad V Potluri Siddhartha Institute of Technology, Vijayawada, India., Tirumanadham NSKMK; Department of Computer Science and Engineering, Sir C R Reddy College of Engineering, Eluru, India., Islam S; Institute of Computer Science and Digital innovation, UCSI University, Kuala Lumpur, Malaysia., Ahmed FRA; Computer Science Department, College of Computer Engineering and Science, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia., Ahmed TE; Computer Science Department, College of Science and Humanities-Jubail, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia., Noboni AA; Department of Surgery, Medical College For Women and Hospital, Dhaka, Bangladesh., Sampedro GA; 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., Yeun CY; Centre for Cyber Physical Systems, Computer Science Department, Khalifa University, Abu Dhabi, United Arab Emirates., Ghazal TM; Faculty of Information Science and Technology, University Kebangsaan Malaysia, Bangi, Selangor, Malaysia.

Publikováno v: Frontiers in medicine [Front Med (Lausanne)] 2024 Jul 05; Vol. 11, pp. 1407376. Date of Electronic Publication: 2024 Jul 05 (Print Publication: 2024).