Prognostic models in COVID-19 infection that predict severity: a systematic review

C Buttia, E Llanaj, H Raeisi-Dehkordi, L Kastrati… - European journal of …, 2023 - Springer
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …

A review on interpretable and explainable artificial intelligence in hydroclimatic applications

H Başağaoğlu, D Chakraborty, CD Lago, L Gutierrez… - Water, 2022 - mdpi.com
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable
Artificial Intelligence (XAI) models for data imputations and numerical or categorical …

Age is the main determinant of COVID-19 related in-hospital mortality with minimal impact of pre-existing comorbidities, a retrospective cohort study

M Henkens, AG Raafs, JAJ Verdonschot, M Linschoten… - BMC geriatrics, 2022 - Springer
Background Age and comorbidities increase COVID-19 related in-hospital mortality risk, but
the extent by which comorbidities mediate the impact of age remains unknown. Methods In …

Neurological and (neuro) psychological sequelae in intensive care and general ward COVID‐19 survivors

S Klinkhammer, J Horn, AA Duits… - European journal of …, 2023 - Wiley Online Library
Background and purpose Coronavirus disease 2019 (COVID‐19) affects the brain, leading
to long‐term complaints. Studies combining brain abnormalities with objective and …

Integrative plasma metabolic and lipidomic modelling of SARS-CoV-2 infection in relation to clinical severity and early mortality prediction

S Lodge, NG Lawler, N Gray, R Masuda… - International Journal of …, 2023 - mdpi.com
An integrative multi-modal metabolic phenotyping model was developed to assess the
systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease …

Mortality and readmission rates among hospitalized COVID-19 patients with varying stages of chronic kidney disease: a multicenter retrospective cohort

B Appelman, JJ Oppelaar, L Broeders, WJ Wiersinga… - Scientific reports, 2022 - nature.com
Chronic kidney disease (CKD) has been recognized as a highly prevalent risk factor for both
the severity of coronavirus disease 2019 (COVID-19) and COVID-19 associated adverse …

Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review

S Shakibfar, F Nyberg, H Li, J Zhao… - Frontiers in Public …, 2023 - frontiersin.org
Aim To perform a systematic review on the use of Artificial Intelligence (AI) techniques for
predicting COVID-19 hospitalization and mortality using primary and secondary data …

[HTML][HTML] Mortality prediction of COVID-19 patients using soft voting classifier

N Rai, N Kaushik, D Kumar, C Raj, A Ali - International Journal of Cognitive …, 2022 - Elsevier
COVID-19 is a novel coronavirus that spread around the globe with the initial reports coming
from Wuhan, China, turned into a pandemic and caused enormous casualties. Various …

[HTML][HTML] Extremely missing numerical data in Electronic Health Records for machine learning can be managed through simple imputation methods considering …

P Ferri, N Romero-Garcia, R Badenes… - Computer Methods and …, 2023 - Elsevier
Abstract Background and objective Reusing Electronic Health Records (EHRs) for Machine
Learning (ML) leads on many occasions to extremely incomplete and sparse tabular …

Machine learning-based derivation and external validation of a tool to predict death and development of organ failure in hospitalized patients with COVID-19

Y Xu, A Trivedi, N Becker, M Blazes, JL Ferres… - Scientific Reports, 2022 - nature.com
COVID-19 mortality risk stratification tools could improve care, inform accurate and rapid
triage decisions, and guide family discussions regarding goals of care. A minority of COVID …