ArticleScientific reports2019
Radiomics Nomogram Analyses for Differentiating Pneumonia and Acute Paraquat Lung Injury.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- CT-based radiomics nomogram for distinguishingTranslational pediatrics · 2026Article
- Machine learning models based on chest computed tomography for identifying plastic bronchitis in children withTranslational pediatrics · 2025Article
- Comparative study of adipose tissue derived mesenchymal stem cells with rapamycin on paraquat-induced acute lung injury and pulmonary fibrosis in a mouse model: histological and biochemical study.Stem cell research & therapy · 2025Article
- Baicalin and lung diseases.Naunyn-Schmiedeberg's archives of pharmacology · 2024Review
- CT‑based radiomics analysis of consolidation characteristics in differentiating pulmonary disease of non‑tuberculous mycobacterium from pulmonary tuberculosis.Experimental and therapeutic medicine · 2024Article
- Quantitative radiomics analysis of imaging features in adults and children Mycoplasma pneumonia.Frontiers in medicine · 2024Article
- A nomogram proposal for early prediction of intensive care unit admission in patients with acute antipsychotic poisoning.Toxicology research · 2023Article
- Potential predictive value of CT radiomics features for treatment response in patients with COVID-19.The clinical respiratory journal · 2023Article
- Development of a radiomics nomogram to predict the treatment resistance of Chinese MPO-AAV patients with lung involvement: a two-center study.Frontiers in immunology · 2023Article
- Development and validation of a nomogram for predicting Mycoplasma pneumoniae pneumonia in adults.Scientific reports · 2022Article
- A CT-based nomogram for differentiating invasive fungal disease of the lung from bacterial pneumonia.BMC medical imaging · 2022Article
- Characterization of Lifetime Agrichemical Exposure Sequences Relative to International Migration in Foreign Born Latinx Agricultural Workers Living in South Florida.Journal of immigrant and minority health · 2022Article
- Differentiating nontuberculous mycobacterium pulmonary disease from pulmonary tuberculosis through the analysis of the cavity features in CT images using radiomics.BMC pulmonary medicine · 2022Article
- Paraquat Induces Lung InjuryFrontiers in pharmacology · 2022Article
- Article
- Development and Validation of a Radiomics Nomogram for Differentiating Mycoplasma Pneumonia and Bacterial Pneumonia.Diagnostics (Basel, Switzerland) · 2021Article
- Can kissing cause paraquat poisoning: A case report and review of literature.World journal of clinical cases · 2021Article
- Early recognition of necrotizing pneumonia in children based on non-contrast-enhanced computed tomography radiomics signatures.Translational pediatrics · 2021Article
- Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients.Computers in biology and medicine · 2021Article
- CT-based radiomics combined with signs: a valuable tool to help radiologist discriminate COVID-19 and influenza pneumonia.BMC medical imaging · 2021Article
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7 authors.
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Abstract
Paraquat poisoning has become a serious public health problem in some Asian countries because of misuse or suicide. We sought to develop and validate a radiomics nomogram incorporating radiomics signature and laboratory bio-markers, for differentiating bacterial pneumonia and acute paraquat lung injury. 180 patients with pneumonia and acute paraquat who underwent CT examinations between December 2014 and October 2017 were retrospectively evaluated for testing and validation. Clinical information including demographic data, clinical symptoms and laboratory test were also recorded. A prediction model was built by using backward logistic regression and presented on a nomogram. The radiomics-based features yielded areas under the receiver operating characteristic curve of 0.870 (95% CI 0.757-0.894), sensitivity of 0.857, specificity of 0.804, positive predictive value of 83.3%, negative predictive value of 0.818 in the primary cohort, while in the validation cohort the model showed similar results (0.865 (95% CI 0.686-0.907), 0.833, 0.792, 81.5%, respectively). The individualized nomogram included radiomics signature, body temperature, nausea and vomiting, and aspartate transaminase. We have developed a radiomics nomogram that combination of the radiomics features and clinical risk factors to differentiate paraquat lung injury and pneumonia for patients with an unclear medical history of exposure to paraquat poisoning, providing appropriate therapy decision support.
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