ArticleMedical image analysis2021
Deep learning for predicting COVID-19 malignant progression.
Article in Medical image analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 5 of them syntheses that pooled it.
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Who cites it
48 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Diagnostic Test Accuracy of Deep Learning Prediction Models on COVID-19 Severity: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2023Pooled 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
- A systematic meta-analysis of immune signatures in patients with COVID-19.Reviews in medical virology · 2021Pooled it
- Artificial Intelligence for COVID-19: A Systematic Review.Frontiers in medicine · 2021Pooled it
- Elevated D-dimer levels on admission are associated with severity and increased risk of mortality in COVID-19: A systematic review and meta-analysis.The American journal of emergency medicine · 2021Pooled it
- Review
- The role of artificial intelligence in managing COVID-19 and long COVID: a narrative review.Osong public health and research perspectives · 2026Article
- Diffusion model-empowered patella shape analysis predicts knee osteoarthritis outcomes.Osteoarthritis and cartilage open · 2025Article
- Infectious Disease Surveillance in the Era of Big Data and AI: Opportunities and Pitfalls.Cureus · 2025Review
- Development and multicentric external validation of a prognostic COVID-19 severity model based on thoracic CT.BMC medical informatics and decision making · 2025Article
- Review of multimodal machine learning approaches in healthcare.An international journal on information fusion · 2025Article
- Prediction of COVID-19 Hospitalization and Mortality Using Artificial Intelligence.Healthcare (Basel, Switzerland) · 2024Article
- Innovative applications of artificial intelligence during the COVID-19 pandemic.Infectious medicine · 2024Review
- Robust Medical Diagnosis: A Novel Two-Phase Deep Learning Framework for Adversarial Proof Disease Detection in Radiology Images.Journal of imaging informatics in medicine · 2024Article
- Visual transformer and deep CNN prediction of high-risk COVID-19 infected patients using fusion of CT images and clinical data.BMC medical informatics and decision making · 2023Article
- Article
- Deep Learning Methods for Interpretation of Pulmonary CT and X-ray Images in Patients with COVID-19-Related Lung Involvement: A Systematic Review.Journal of clinical medicine · 2023Review
- Bibliometric analysis of the use of artificial intelligence in COVID-19 based on scientific studies.Health science reports · 2023Article
- Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes.Computers in biology and medicine · 2023Article
- Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosis and treatment, which has greatly challenged public medical systems. Treatment priority is often determined by the symptom severity based on first assessment. However, clinical observation suggests that some patients with mild symptoms may quickly deteriorate. Hence, it is crucial to identify patient early deterioration to optimize treatment strategy. To this end, we develop an early-warning system with deep learning techniques to predict COVID-19 malignant progression. Our method leverages CT scans and the clinical data of outpatients and achieves an AUC of 0.920 in the single-center study. We also propose a domain adaptation approach to improve the generalization of our model and achieve an average AUC of 0.874 in the multicenter study. Moreover, our model automatically identifies crucial indicators that contribute to the malignant progression, including Troponin, Brain natriuretic peptide, White cell count, Aspartate aminotransferase, Creatinine, and Hypersensitive C-reactive protein.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.