Related Experiment Video
Updated: Dec 14, 2025
Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Predicting Clinical Outcomes in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A
Artificial intelligence models using chest X-rays accurately predict COVID-19 patient outcomes, including mechanical ventilation needs and mortality. Combining AI with radiologist scores improved prediction accuracy, aiding clinical decisions.
Area of Science:
- Radiology
- Artificial Intelligence
- Computational Pathology
Background:
- Coronavirus disease 2019 (COVID-19) poses significant challenges in predicting patient outcomes.
- Accurate prediction of mechanical ventilation requirement and mortality is crucial for patient management and resource allocation.
Conclusions:
- Computational models utilizing chest radiographs show significant promise in predicting mechanical ventilation requirement and mortality in COVID-19 patients.
- Combined approaches leveraging both AI (radiomics, DL) and expert radiologist interpretation offer superior prognostic information compared to either method alone.
- These AI-driven prognostic tools can potentially support clinical decision-making and optimize resource allocation during public health crises like the COVID-19 pandemic.
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