ArticleCancers2021
Deep Learning Algorithm Trained with COVID-19 Pneumonia Also Identifies Immune Checkpoint Inhibitor Therapy-Related Pneumonitis.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- CT-based deep foundation model for predicting immune checkpoint inhibitor-induced pneumonitis risk in lung cancer.Journal for immunotherapy of cancer · 2026Article
- Differentiating Immune Checkpoint Inhibitor-Related Pneumonitis from COVID-19 Pneumonia Using a CT-based Radiomics Nomogram.Current medical imaging · 2025Article
- Article
- Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography.JCO clinical cancer informatics · 2025Article
- Lung field-based severity score (LFSS): a feasible tool to identify COVID-19 patients at high risk of progressing to critical disease.Journal of thoracic disease · 2024Article
- ChatGPT in radiology structured reporting: analysis of ChatGPT-3.5 Turbo and GPT-4 in reducing word count and recalling findings.Quantitative imaging in medicine and surgery · 2024Article
- Classification of Alzheimer disease using DenseNet-201 based on deep transfer learning technique.PloS one · 2024Article
- Impact of Quantitative Computed Tomography-Based Analysis of Abdominal Adipose Tissue in Patients with Lymphoma.Hematology reports · 2023Article
- Computed tomography density changes of bone metastases after concomitant denosumab.Skeletal radiology · 2023Article
- Large language models for structured reporting in radiology: performance of GPT-4, ChatGPT-3.5, Perplexity and Bing.La Radiologia medica · 2023Article
- Adverse Effects of Immune-Checkpoint Inhibitors: A Comprehensive Imaging-Oriented Review.Current oncology (Toronto, Ont.) · 2023Review
- Artificial intelligence and radiomics: fundamentals, applications, and challenges in immunotherapy.Journal for immunotherapy of cancer · 2022Review
- Epicardial and pericardial fat analysis on CT images and artificial intelligence: a literature review.Quantitative imaging in medicine and surgery · 2022Review
- Novel Magnetic Resonance Imaging Tools for the Diagnosis of Degenerative Disc Disease: A Narrative Review.Diagnostics (Basel, Switzerland) · 2022Review
- A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions.Sensors (Basel, Switzerland) · 2021Review
- Artificial intelligence and abdominal adipose tissue analysis: a literature review.Quantitative imaging in medicine and surgery · 2021Review
- Radiation-Induced Lung Injury-Current Perspectives and Management.Clinics and practice · 2021Review
- Radiation-Induced Pneumonitis in the Era of the COVID-19 Pandemic: Artificial Intelligence for Differential Diagnosis.Cancers · 2021Article
- Article
- Review of deep learning: concepts, CNN architectures, challenges, applications, future directions.Journal of big data · 2021Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoronavirus disease 2019 (COVID-19) pneumonia and immune checkpoint inhibitor (ICI) therapy-related pneumonitis share common features. The aim of this study was to determine on chest computed tomography (CT) images whether a deep convolutional neural network algorithm is able to solve the challenge of differential diagnosis between COVID-19 pneumonia and ICI therapy-related pneumonitis.
methodsWe enrolled three groups: a pneumonia-free group (
resultsThe algorithm showed low specificity in distinguishing COVID-19 from ICI therapy-related pneumonitis (sensitivity 97.1%, specificity 14.3%, area under the curve (AUC) = 0.62). ICI therapy-related pneumonitis was identified by the AI when compared to pneumonia-free controls (sensitivity = 85.7%, specificity 100%, AUC = 0.97).
conclusionsThe deep learning algorithm is not able to distinguish between COVID-19 pneumonia and ICI therapy-related pneumonitis. Awareness must be increased among clinicians about imaging similarities between COVID-19 and ICI therapy-related pneumonitis. ICI therapy-related pneumonitis can be applied as a challenge population for cross-validation to test the robustness of AI models used to analyze interstitial pneumonias of variable etiology.
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