Systematic review on missing data imputation techniques with machine learning algorithms for healthcare

• Main Authors: Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Maen, Mohd Khaled
• Format: Article
• Language: English; English
• Published: Department of Electrical Engineering, Universitas Muhammadiyah Yogyakarta 2022
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://irep.iium.edu.my/98894/7/98894_Systematic%20review%20on%20missing%20data%20imputation%20techniques_SCOPUS.pdf; http://irep.iium.edu.my/98894/8/98894_Systematic%20review%20on%20missing%20data%20imputation%20techniques.pdf; http://irep.iium.edu.my/98894/; https://journal.umy.ac.id/index.php/jrc/article/download/13133/7111

Missing data is one of the most common issues encountered in data cleaning process especially when dealing with medical dataset. A real collected dataset is prone to be incomplete, inconsistent, noisy and redundant due to potential reasons such as human errors, instrumental failures, and adverse dea...