• Feb 07, 2023 News!JACN will adopt Article-by-Article Work Flow. The benefit of article-by-article workflow is that a delay with one article may not delay the entire issue. Once a paper steps into production, it will be published online soon.   [Click]
  • May 30, 2022 News!JACN Vol.10, No.1 has been published with online version.   [Click]
  • Dec 24, 2021 News!Volume 9 No 1 has been indexed by EI (inspec)!   [Click]
General Information
    • ISSN: 1793-8244 (Print)
    • Abbreviated Title:  J. Adv. Comput. Netw.
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Professor Haklin Kimm
    • Executive Editor: Ms. Cherry Chan
    • Abstracting/ Indexing: EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
    • APC: 500USD
Professor Haklin Kimm
East Stroudsburg University, USA
I'm happy to take on the position of editor in chief of JACN. We encourage authors to submit papers on all aspects of computer networks.

JACN 2019 Vol.7(1): 13-17 ISSN: 1793-8244
DOI: 10.18178/JACN.2019.7.1.265

A Distance-Threshold kNN Method for Imputing Medical Data Missing Values

Ching-Hsue Cheng and Hao-Hsuan Huang

Abstract—In medical filed, missing data often existed, which maybe result in the bias of research results. Therefore, this study proposes a new imputation method, that is a nearest neighborhood method based on distance threshold to impute missing value. The proposed imputation method has two merits: (1) utilize distance threshold to adjust the optimal nearest neighborhood for estimating missing values, (2) the proposed method compares with other imputation methods in medical data missing values. This study collected the stroke dataset from the International Stroke Trial (IST) to verify the proposed method, the result shows that the proposed method is better than other imputation methods, it means that the proposed method can be effectively utilized in practical medical dataset.

Index Terms—Missing value, imputation, nearest neighborhood, stroke disease.

Ching-Hsue Cheng and Hao-Hsuan Huang are with Department of Information Management, National Yunlin University of Science & Technology, 123, section 3, University Road, Touliu, Yunlin, 640, Taiwan (e-mail: chcheng@yuntech.edu.tw, liang50641@gmail.com).


Cite:Ching-Hsue Cheng and Hao-Hsuan Huang, "A Distance-Threshold kNN Method for Imputing Medical Data Missing Values," Journal of Advances in Computer Networks vol. 7, no. 1, pp. 13-17, 2019.

Copyright © 2008-2024. Journal of Advances in Computer Networks.  All rights reserved.
E-mail: jacn@ejournal.net