Cargando…

Correction to: Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures

Detalles Bibliográficos
Autores principales:	Wang, Hongmei, Wang, Lu, Lee, Edward H., Zheng, Jimmy, Zhang, Wei, Halabi, Safwan, Liu, Chunlei, Deng, Kexue, Song, Jiangdian, Yeom, Kristen W.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2021
Materias:	Correction
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7925806/ https://www.ncbi.nlm.nih.gov/pubmed/33656580 http://dx.doi.org/10.1007/s00259-021-05268-5

Ejemplares similares

Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures
por: Wang, Hongmei, et al.
Publicado: (2020)

Correction to: End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT
por: Song, Jiangdian, et al.
Publicado: (2021)

Multi-classifier-based identification of COVID-19 from chest computed tomography using generalizable and interpretable radiomics features
por: Wang, Lu, et al.
Publicado: (2021)

End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT
por: Song, Jiangdian, et al.
Publicado: (2020)

A general approach for automatic segmentation of pneumonia, pulmonary nodule, and tuberculosis in CT images
por: Wang, Lu, et al.
Publicado: (2023)

Decoding and Systematization of Medical Imaging Features of Multiple Human Malignancies
por: Wang, Lu, et al.
Publicado: (2020)

Decoding tumor mutation burden and driver mutations in early stage lung adenocarcinoma using CT‐based radiomics signature
por: Wang, Xiaoxiao, et al.
Publicado: (2019)

Decoding intra-tumoral spatial heterogeneity on radiological images using the Hilbert curve
por: Wang, Lu, et al.
Publicado: (2021)

Correction for Ornes, Researchers turn to deep learning to decode protein structures
Publicado: (2022)

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia
por: Li, Liang, et al.
Publicado: (2021)

Correction: Radiomics analysis based on CT for the prediction of pulmonary metastases in ewing sarcoma
por: Liu, Ying, et al.
Publicado: (2023)

A deep learning-based system for survival benefit prediction of tyrosine kinase inhibitors and immune checkpoint inhibitors in stage IV non-small cell lung cancer patients: A multicenter, prognostic study
por: Deng, Kexue, et al.
Publicado: (2022)

CT-based deep learning radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer
por: Chen, Weitian, et al.
Publicado: (2022)

2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer
por: Shen, Chen, et al.
Publicado: (2017)

Correction: Decoding Vigilance with NIRS
Publicado: (2015)

Neuroendocrine Carcinoma of the Urinary Bladder: CT Findings and Radiomics Signature
por: Coppola, Andrea, et al.
Publicado: (2023)

CT-Based Radiomics Signatures for Predicting the Risk Categorization of Thymic Epithelial Tumors
por: Liu, Jin, et al.
Publicado: (2021)

Comparison of deep learning, radiomics and subjective assessment of chest CT findings in SARS-CoV-2 pneumonia
por: Arru, Chiara, et al.
Publicado: (2021)

Correction to: Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma
por: Röhrich, Sebastian, et al.
Publicado: (2021)

CT radiomic models to distinguish COVID-19 pneumonia from other interstitial pneumonias
por: Cardobi, Nicolò, et al.
Publicado: (2021)

Development and Validation of an Automated Radiomic CT Signature for Detecting COVID-19
por: Guiot, Julien, et al.
Publicado: (2020)

Correction to: Co‑clinical FDG‑PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple‑negative breast cancer
por: Roy, Sudipta, et al.
Publicado: (2021)

Correction: A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management
por: Anan, Noushin, et al.
Publicado: (2022)

The value of CT radiomic in differentiating mycoplasma pneumoniae pneumonia from streptococcus pneumoniae pneumonia with similar consolidation in children under 5 years
por: Wang, Dongdong, et al.
Publicado: (2022)

Author Correction: Radiomics feature reproducibility under inter-rater variability in segmentations of CT images
por: Haarburger, Christoph, et al.
Publicado: (2021)

The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT
por: Xiong, Fei, et al.
Publicado: (2021)

Correction: A novel intelligent radiomic analysis of perfusion SPECT/CT images to optimize pulmonary embolism diagnosis in COVID-19 patients
por: Baeza, Sonia, et al.
Publicado: (2023)

Current Applications of Deep Learning and Radiomics on CT and CBCT for Maxillofacial Diseases
por: Hung, Kuo Feng, et al.
Publicado: (2022)

CT-based deep learning segmentation of ovarian cancer and the stability of the extracted radiomics features
por: Wang, Yiang, et al.
Publicado: (2023)

Attention-guided deep learning for gestational age prediction using fetal brain MRI
por: Shen, Liyue, et al.
Publicado: (2022)

CT-Based Radiomics Signature With Machine Learning Predicts MYCN Amplification in Pediatric Abdominal Neuroblastoma
por: Chen, Xin, et al.
Publicado: (2021)

Correction to ‘Optocoder: computational decoding of spatially indexed bead arrays’
Publicado: (2023)

Author Correction: A computerized diagnostic model for automatically evaluating placenta accrete spectrum disorders based on the combined MR radiomics-clinical signatures
por: Zhu, Hao, et al.
Publicado: (2022)

Nomograms integrating CT radiomic and deep learning signatures to predict overall survival and progression-free survival in NSCLC patients treated with chemotherapy
por: Chang, Runsheng, et al.
Publicado: (2023)

Author Correction: Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer
por: Zheng, Xueyi, et al.
Publicado: (2021)

Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer
por: Xu, Xiaopan, et al.
Publicado: (2021)

Correction: Transcriptional Blood Signatures Distinguish Pulmonary Tuberculosis, Pulmonary Sarcoidosis, Pneumonias and Lung Cancers
por: Bloom, Chloe I., et al.
Publicado: (2013)

A CT-Based Radiomic Signature for the Differentiation of Pulmonary Hamartomas from Carcinoid Tumors
por: Cangir, Ayten Kayi, et al.
Publicado: (2022)

CT angiographic radiomics signature for risk stratification in anterior large vessel occlusion stroke
por: Avery, Emily W., et al.
Publicado: (2022)

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign
por: Xu, Hang, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_9u2ftku2umfbgc6nk7ht4qjns1