Systematic review of advanced AI methods for improving healthcare data quality in post COVID-19 Era

M Isgut, L Gloster, K Choi… - IEEE Reviews in …, 2022 - ieeexplore.ieee.org
At the beginning of the COVID-19 pandemic, there was significant hype about the potential
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …

A deep learning–based unsupervised method to impute missing values in patient records for improved management of cardiovascular patients

D Xu, JQ Sheng, PJH Hu, TS Huang… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Physicians increasingly depend on electronic health records (EHRs) to manage their
patients. However, many patient records have substantial missing values that pose a …

Entering the new digital era of intensive care medicine: an overview of interdisciplinary approaches to use artificial intelligence for patients' benefit

O Old, B Friedrichson, K Zacharowski… - European Journal of …, 2023 - journals.lww.com
The idea of implementing artificial intelligence in medicine is as old as artificial intelligence
itself. So far, technical difficulties have prevented the integration of artificial intelligence in …

A novel model to optimize multiple imputation algorithm for missing data using evolution methods

YS Mohammed, H Abdelkader, P Pławiak… - … Signal Processing and …, 2022 - Elsevier
The concept of missing data is considered significant when applying statistical methods to a
dataset and the quality of the data analysis results is based on the correct data …

A survey of machine learning-based approaches for missing value imputation

VK Gond, A Dubey, A Rasool - 2021 third international …, 2021 - ieeexplore.ieee.org
Missing values create issues during the analysis of the dataset. Learning algorithms in an
asymmetrical dataset can generate an overrated classification accuracy due to a bias …

A novel neural network for improved in-hospital mortality prediction with irregular and incomplete multivariate data

X Zhou, W Xiang, T Huang - Neural Networks, 2023 - Elsevier
Accurate estimation of in-hospital mortality based on patients' physiological time series data
improves the performance of the clinical decision support systems and assists hospital …

Explainable dynamic multimodal variational autoencoder for the prediction of patients with suspected central precocious puberty

Y Xu, X Liu, L Pan, X Mao, H Liang… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Central precocious puberty (CPP) is the most common type of precocious puberty and has a
significant effect on children. A gonadotropin-releasing hormone (GnRH)-stimulation test is …

Hybrid diabetes disease prediction framework based on data imputation and outlier detection techniques

AK Srivastava, Y Kumar, PK Singh - Expert Systems, 2022 - Wiley Online Library
In the field of medical science, accurate prediction is a difficult and challenging task. But, the
presence of missing values and outliers can make the prediction task more complicated …

Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification

G Vivar, A Kazi, H Burwinkel, A Zwergal… - Artificial intelligence in …, 2021 - Elsevier
Large-scale population-based studies in medicine are a key resource towards better
diagnosis, monitoring, and treatment of diseases. They also serve as enablers of clinical …

Artificial neural network-based data imputation for handling anomalous energy consumption readings in smart homes

K Purna Prakash, YVP Kumar… - Energy Exploration …, 2024 - journals.sagepub.com
Smart homes are at the forefront of sustainable living, utilizing advanced monitoring systems
to optimize energy consumption. However, these systems frequently encounter issues with …