ArticleScientific reports2021
Study on the prognosis predictive model of COVID-19 patients based on CT radiomics.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Automated COVID-19 diagnosis and prognosis with medical imaging and who is publishing: a systematic review.Physical and engineering sciences in medicine · 2022Pooled it
- Prediction of potential severe coronavirus disease 2019 patients based on CT radiomics: A retrospective study.Medical physics · 2022Trial
- CT-based radiomics nomogram for distinguishingTranslational pediatrics · 2026Article
- CT-based radiomics models for predicting the prognosis of children with mycoplasma pneumonia.Frontiers in cellular and infection microbiology · 2026Article
- Mathematical models to characterize the early phase of the COVID-19 pandemic in New Mexico, USA.Mathematical biosciences and engineering : MBE · 2025Article
- Article
- Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review.Bioengineering (Basel, Switzerland) · 2025Review
- Development and multicentric external validation of a prognostic COVID-19 severity model based on thoracic CT.BMC medical informatics and decision making · 2025Article
- Article
- Article
- Efficient clinical decision-making process via AI-based multimodal data fusion: A COVID-19 case study.Heliyon · 2024Article
- Identifying severe community-acquired pneumonia using radiomics and clinical data: a machine learning approach.Scientific reports · 2024Article
- Multimodal graph attention network for COVID-19 outcome prediction.Scientific reports · 2023Article
- Prognosis Prediction in COVID-19 Patients through Deep Feature Space Reasoning.Diagnostics (Basel, Switzerland) · 2023Article
- Immunohematologic Biomarkers in COVID-19: Insights into Pathogenesis, Prognosis, and Prevention.Pathogens & immunity · 2023Review
- Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?BMC medical imaging · 2022Article
- Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.Scientific reports · 2022Article
- Clinical characteristics and outcomes of hospitalized patients with COVID-19 in a Brazilian hospital: a retrospective study of the first and second waves.IJID regions · 2022Article
- CT-based radiomics in predicting pathological response in non-small cell lung cancer patients receiving neoadjuvant immunotherapy.Frontiers in oncology · 2022Article
- Dense Convolutional Network and Its Application in Medical Image Analysis.BioMed research international · 2022Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Making timely assessments of disease progression in patients with COVID-19 could help offer the best personalized treatment. The purpose of this study was to explore an effective model to predict the outcome of patients with COVID-19. We retrospectively included 188 patients (124 in the training set and 64 in the test set) diagnosed with COVID-19. Patients were divided into aggravation and improvement groups according to the disease progression. Three kinds of models were established, including the radiomics, clinical, and combined model. Receiver operating characteristic curves, decision curves, and Delong's test were used to evaluate and compare the models. Our analysis showed that all the established prediction models had good predictive performance in predicting the progress and outcome of COVID-19.
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