A data-driven missing value imputation approach for longitudinal datasets
Sign Up to like & getrecommendations! Published in 2021 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-021-09963-5
Abstract: Longitudinal datasets of human ageing studies usually have a high volume of missing data, and one way to handle missing values in a dataset is to replace them with estimations. However, there are many methods… read more here.
Keywords: imputation; driven missing; missing value; data driven ... See more keywords
Missing Value Imputation Designs and Methods of Nature-Inspired Metaheuristic Techniques: A Systematic Review
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3172319
Abstract: Missing values are highly undesirable in real-world datasets. The missing values should be estimated and treated during the preprocessing stage. With the expansion of nature-inspired metaheuristic techniques, interest in missing value imputation (MVI) has increased.… read more here.
Keywords: nature inspired; inspired metaheuristic; review; missing value ... See more keywords
Missing Value Imputation Methods for Electronic Health Records
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3251919
Abstract: Electronic health records (EHR) are patient-level information, e.g., laboratory tests and questionnaires, stored in electronic format. Compared to physical records, the EHR alternative allows patients to access their data easily and helps staff with management… read more here.
Keywords: health records; missing value; value imputation; electronic health ... See more keywords
GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies
Sign Up to like & getrecommendations! Published in 2018 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1005973
Abstract: Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However,… read more here.
Keywords: censored missing; left censored; value imputation; missing value ... See more keywords
An Improved Bi-LSTM-Based Missing Value Imputation Approach for Pregnancy Examination Data
Sign Up to like & getrecommendations! Published in 2022 at "Algorithms"
DOI: 10.3390/a16010012
Abstract: In recent years, the development of computer technology has promoted the informatization and intelligentization of hospital management systems and thus produced a large amount of medical data. These medical data are valuable resources for research.… read more here.
Keywords: examination data; missing value; value imputation; pregnancy ... See more keywords