Preliminary Simulation for Obtaining Accurate Heart Rate Data Using Imputation Methods

被引：0
|
作者：
Ramnarine-Rieks, Angela [1 ]
Deshmukh, Avin [1 ]
Sang, Yisi [1 ]
Lugo, Daniel [1 ]
Xu, Sichun [1 ]
机构：
[1] Syracuse University, United States
来源：
Proceedings of the Association for Information Science and Technology | 2021年 / 58卷 / 01期
关键词：
7;
D O I：
10.1002/pra2.570
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：808 / 810
相关论文
共 50 条
  • [1] Improving Accuracy Rate of Imputation of Missing Data using Classifier Methods
    Thirukumaran, S.
    Sumathi, A.
    PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND CONTROL (ISCO'16), 2016,
  • [2] Missing-data imputation using wearable sensors in heart rate variability
    Tlija, A.
    Wegrzyn-Wolska, K.
    Istrate, D.
    BULLETIN OF THE POLISH ACADEMY OF SCIENCES-TECHNICAL SCIENCES, 2020, 68 (02) : 255 - 261
  • [3] Comparison of Missing Data Imputation Methods using the Framingham Heart study dataset
    Psychogyios, Konstantinos
    Ilias, Loukas
    Askounis, Dimitris
    2022 IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI) JOINTLY ORGANISED WITH THE IEEE-EMBS INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN'22), 2022,
  • [4] Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation
    Choudhury, Olivia
    Chakrabarty, Ankush
    Emrich, Scott J.
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2019, 16 (04) : 1107 - 1116
  • [5] Comparison of missing data imputation methods using weather data
    Nida, Hafiza
    Kashif, Muhammad
    Khan, Muhammad Imran
    Ghamkhar, Madiha
    PAKISTAN JOURNAL OF AGRICULTURAL SCIENCES, 2023, 60 (02): : 327 - 336
  • [6] A simulation comparison of imputation methods for quantitative data in the presence of multiple data patterns
    Solaro, N.
    Barbiero, A.
    Manzi, G.
    Ferrari, P. A.
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2018, 88 (18) : 3588 - 3619
  • [7] A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methods
    Ge, Yingfeng
    Li, Zhiwei
    Zhang, Jinxin
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [8] A simulation study on missing data imputation for dichotomous variables using statistical and machine learning methods
    Yingfeng Ge
    Zhiwei Li
    Jinxin Zhang
    Scientific Reports, 13
  • [9] New imputation methods for missing data using quantiles
    Munoz, J. F.
    Rueda, M.
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2009, 232 (02) : 305 - 317
  • [10] Handling Incomplete Data Using Evolution of Imputation Methods
    Zawistowski, Pawel
    Grzenda, Maciej
    ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, 2009, 5495 : 22 - +
12345