ArticleiScience2021
A deep learning approach for predicting severity of COVID-19 patients using a parsimonious set of laboratory markers.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Machine learning-based risk prediction of outcomes in patients hospitalized with COVID-19 in Australia: the AUS-COVID Score.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers.Scientific reports · 2025Article
- Evaluating the impact of common clinical confounders on performance of deep-learning-based sepsis risk assessment.Frontiers in artificial intelligence · 2025Article
- Feature Identification Using Interpretability Machine Learning Predicting Risk Factors for Disease Severity of In-Patients with COVID-19 in South Florida.Diagnostics (Basel, Switzerland) · 2024Article
- Concordance and generalization of an AI algorithm with real-world clinical data in the pre-omicron and omicron era.Heliyon · 2024Article
- The Diagnostic, Prognostic, and Therapeutic Potential of Cell-Free DNA with a Special Focus on COVID-19 and Other Viral Infections.International journal of molecular sciences · 2023Review
- Diagnosis of COVID-19 Using Chest X-ray Images and Disease Symptoms Based on Stacking Ensemble Deep Learning.Diagnostics (Basel, Switzerland) · 2023Article
- The COVID-19 pandemic in various restriction policy scenarios based on the dynamic social contact rate.Heliyon · 2023Article
- Generalizable machine learning approach for COVID-19 mortality risk prediction using on-admission clinical and laboratory features.Scientific reports · 2023Article
- Overt and Occult Hypoxemia in Patients Hospitalized With COVID-19.Critical care explorations · 2023Article
- Biomarkers extracted by fully automated body composition analysis from chest CT correlate with SARS-CoV-2 outcome severity.Scientific reports · 2022Article
- Overt and occult hypoxemia in patients hospitalized with novel coronavirus disease 2019.medRxiv : the preprint server for health sciences · 2022Article
- Prediction of COVID-19 Patients' Survival by Deep Learning Approaches.Medical journal of the Islamic Republic of Iran · 2022Article
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Authors and funding
11 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The SARS-CoV-2 virus has caused tremendous healthcare burden worldwide. Our focus was to develop a practical and easy-to-deploy system to predict the severe manifestation of disease in patients with COVID-19 with an aim to assist clinicians in triage and treatment decisions. Our proposed predictive algorithm is a trained artificial intelligence-based network using 8,427 COVID-19 patient records from four healthcare systems. The model provides a severity risk score along with likelihoods of various clinical outcomes, namely ventilator use and mortality. The trained model using patient age and nine laboratory markers has the prediction accuracy with an area under the curve (AUC) of 0.78, 95% CI: 0.77-0.82, and the negative predictive value NPV of 0.86, 95% CI: 0.84-0.88 for the need to use a ventilator and has an accuracy with AUC of 0.85, 95% CI: 0.84-0.86, and the NPV of 0.94, 95% CI: 0.92-0.96 for predicting in-hospital 30-day mortality.
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