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All Journal International Journal of Psychology and Health Science
Ade Irma Suryani
Rekam Medis dan Informasi Kesehatan Piksi Ganesha Politechnic, Bandung, Indonesia.
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Hybrid Methods for Feature Selection Algorithms in the Field of Medical Records Yuda Syahidin; Ade Irma Suryani
International Journal of Psychology and Health Science Vol. 1 No. 3 (2023): International Journal of Psychology and Health Science (July - September 2023)
Publisher : Greenation Publisher & Yayasan Global Research National

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/ijphs.v1i3.339

Abstract

Big data growth in the healthcare community, accurate analysis of medical data supports early disease detection, patient care and community services. However, the accuracy of the analysis decreases when the quality of the medical data is incomplete. Feature selection is a process that selects a subset of features that are relevant for a predictive modeling problem. This method can identify and remove unnecessary, irrelevant, and redundant attributes from the dataset, which do not contribute to the accuracy of the model or reduce the accuracy of the model. The challenge in research in the field of medical records is in structured and unstructured data which results in a method being needed to assist the algorithm in selecting good features. This paper provides an overview of the proposed hybrid method that can be used for feature selection algorithms in the field of medical records.
Co-Authors Yuda Syahidin