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A Benchmark for Data Imputation Methods [PDF]
Frontiers in Big Data, 2021 With the increasing importance and complexity of data pipelines, data quality became one of the key challenges in modern software applications. The importance of data quality has been recognized beyond the field of data engineering and database ...
Sebastian Jäger +2 more
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A comparison of imputation methods for categorical data
Informatics in Medicine Unlocked, 2023 Objectives: Missing data is commonplace in clinical databases, which are being increasingly used for research. Without giving any regard to missing data, results from analysis may become biased and unrepresentative.
Shaheen MZ. Memon +2 more
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Evaluating imputation methods for single-cell RNA-seq data [PDF]
BMC Bioinformatics, 2023 Background Single-cell RNA sequencing (scRNA-seq) enables the high-throughput profiling of gene expression at the single-cell level. However, overwhelming dropouts within data may obscure meaningful biological signals.
Yi Cheng +4 more
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A model-agnostic framework for dataset-specific selection of missing value imputation methods in pain-related numerical data [PDF]
Canadian Journal of PainMissing value imputation is a routine step in biomedical data analysis, yet techniques are often not tailored to specific datasets. We propose a systematic framework for selecting imputation methods customized for the unique characteristics of cross ...
Jörn Lötsch, Alfred Ultsch
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Deep Learning Methods for Omics Data Imputation
Biology, 2023 One common problem in omics data analysis is missing values, which can arise due to various reasons, such as poor tissue quality and insufficient sample volumes.
Lei Huang +6 more
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Multi-metric comparison of machine learning imputation methods with application to breast cancer survival [PDF]
BMC Medical Research MethodologyHandling missing data in clinical prognostic studies is an essential yet challenging task. This study aimed to provide a comprehensive assessment of the effectiveness and reliability of different machine learning (ML) imputation methods across various ...
Imad El Badisy +3 more
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Mathematics, 2023 The Industrial Internet of Things (IIoT), which integrates sensors into the manufacturing system, provides new paradigms and technologies to industry.
Minh Hung Ho +7 more
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A Systematic Literature Review On Missing Values: Research Trends, Datasets, Methods and Frameworks [PDF]
E3S Web of Conferences, 2023 Handling of missing values in data analysis is the focus of attention in various research fields. Imputation is one method that is commonly used to overcome this problem of missing data.
Setiawan Ismail +2 more
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A Pragmatic Ensemble Strategy for Missing Values Imputation in Health Records
Entropy, 2022 Pristine and trustworthy data are required for efficient computer modelling for medical decision-making, yet data in medical care is frequently missing.
Shivani Batra +5 more
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A Bayesian Approach for Imputation of Censored Survival Data
Stats, 2022 A common feature of much survival data is censoring due to incompletely observed lifetimes. Survival analysis methods and models have been designed to take account of this and provide appropriate relevant summaries, such as the Kaplan–Meier plot and the ...
Shirin Moghaddam +2 more
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