Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography

Cited by (916)

Items 601–700 of 916

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3. Orthonormal Bayesian Convolutional Neural Network for Detection of the Novel Coronavirus-19
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4. Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT’s Semantic Segmentation
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5. Electronic Biosignal Monitoring System for the Prevention of Respiratory Diseases by Applying Artificial Intelligence
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6. Collective intelligent strategy for improved segmentation of COVID-19 from CT
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7. AUTOMATIC MEASUREMENT OF CT NUMBER LINEARITY IN THREE TYPES OF CATPHAN PHANTOMS
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8. Dmbg-Net: Dilated multiresidual boundary guidance network for COVID-19 infection segmentation
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9. Graph Convolution and Self-attention Enhanced CNN with Domain Adaptation for Multi-site COVID-19 Diagnosis
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10. Multi-national CT image-label pairs synthesis for COVID-19 diagnosis via few-shot generative adversarial networks adaptation
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11. Artificial intelligence-based analysis of the spatial distribution of abnormal computed tomography patterns in SARS-CoV-2 pneumonia: association with disease severity
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12. Visual Knowledge Domain of Artificial Intelligence in Computed Tomography: A Review Based on Bibliometric Analysis
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13. CoSev: Data-Driven Optimizations for COVID-19 Severity Assessment in Low-Sample Regimes
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14. Deep Learning Based Fetal Brain Ventricle Segmentation and Size Estimation
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15. Investigation on super-resolution reconstruction of lung CT images for COVID-19 based on sequential images
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16. Assessing the impact of comorbidities on disease severity in COVID-19 patients requires consideration of age
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17. Non-invasive assessment of endothelial dysfunction: A novel method to predict severe COVID-19?
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18. Chest Computed Tomography Scoring in Patients With Novel Coronavirus-infected Pneumonia: Correlation With Clinical and Laboratory Features and Disease Outcome
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19. COVID-view: Diagnosis of COVID-19 using Chest CT
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20. Mix-and-Interpolate: A Training Strategy to Deal With Source-Biased Medical Data
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21. Diagnosing COVID-19 From Chest CT Scan Images Using Deep Learning Models
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22. A Novel Implementation of Machine Learning for the Efficient, Explainable Diagnosis of COVID-19 from Chest CT
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23. Prognostic value of radiological index and clinical data in patients with COVID-19 infection
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24. Development and external validation of a deep learning-based computed tomography classification system for COVID-19
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25. Hybridization of particle swarm optimization algorithm with neural network for COVID‐19 using computerized tomography scan and clinical parameters
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26. Automated Triage Of Covid-19 From Various Lung Abnormalities Using Chest Ct Features
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27. COVIDNet-CT: Detection of COVID-19 from Chest CT Images using a Tailored Deep Convolutional Neural Network Architecture
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28. Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks
    Aditya Killekar, Kajetan Grodecki, Andrew Lin, Sebastien J. Cadet, Priscilla A. McElhinney, Aryabod Razipour, Cato Chan, Barry D. Pressman, Peter J. Julien, Peter Chen et al. · 2022 · Journal of medical imaging
29. Assessment of a deep learning model for COVID-19 classification on chest radiographs: a comparison across image acquisition techniques and clinical factors
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30. Lightweight Model for the Prediction of COVID-19 Through the Detection and Segmentation of Lesions in Chest CT Scans
    Aram Ter-Sarkisov · 2021 · International Journal of Automation Artificial Intelligence and Machine Learning
31. A chest radiography-based artificial intelligence deep-learning model to predict severe Covid-19 patient outcomes: the CAPE (Covid-19 AI Predictive Engine) Model
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32. A New Screening Method for COVID-19 based on Ocular Feature Recognition by Machine Learning Tools
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33. Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images
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34. Diagnosis/Prognosis of COVID-19 Images: Challenges, Opportunities, and Applications
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35. Probabilistic combination of eigenlungs-based classifiers for COVID-19 diagnosis in chest CT images
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36. Explainability Guided Multi-Site COVID-19 CT Classification
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37. Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks
    Kajetan Grodecki, Aditya Killekar, Andrew Lin, Sebastien J. Cadet, Priscilla A. McElhinney, Aryabod Razipour, Cato Chan, Barry D. Pressman, Peter J. Julien, Judit Simon et al. · 2021 · PubMed
38. Single-Shot Lightweight Model For The Detection of Lesions And The Prediction of COVID-19 From Chest CT Scans
    Aram Ter-Sarkisov · 2020 · medRxiv
39. Exploring Machine Learning Strategies in COVID-19 Prognostic Modelling: A Systematic Analysis of Diagnosis, Classification and Outcome Prediction
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40. Self-Supervised Medical Adversarial Robustness With Two-Stage Contrastive Constraints
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41. A machine learning approach for improved resource allocation in COVID-19 ICUs using HRCT scans and clinical data
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42. Performance of AI Approaches for COVID-19 Diagnosis Using Chest CT Scans: The Impact of Architecture and Dataset
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43. Multi-period prediction of residual lung lesions in COVID-19 survivors with multi-head temporal constrained network
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44. Early pneumoconiosis recognition from CT via progressive lesion awareness and multi-axis denoising attention mechanisms
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46. Inflammasomes meet organoids and artificial intelligence: unraveling the complexity of gynecological inflammation
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47. Artificial Intelligence Applications in Pneumonia: Diagnosis and Outcome Prediction
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49. Longitudinal alignments and syntheses of multimodal clinical data for personalized medicine with the PULSE framework
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50. Covid-19 Chest CT Scan Image Classification Using LCKSVD and Frozen Sparse Coding
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53. DACov: a deeper analysis of data augmentation on the computed tomography segmentation problem
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54. COVID-19 Diagnosis in 3D Chest CT Scans with Attention-Based Models
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55. CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations
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56. Quantification of pulmonary opacities using artificial intelligence in chest CT scans during SARS-CoV-2 pandemic: validation and prognostic assessment
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60. Enhancing multiclass pneumonia classification with Machine Learning and textural features
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61. An Intelligent System of Predicting Lymph Node Metastasis in Colorectal Cancer Using 3D CT Scans
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62. FGM-SPCL: Open-Set Recognition Network for Medical Images Based on Fine-Grained Data Mixture and Spatial Position Constraint Loss
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63. 3Cs: Unleashing Capsule Networks for Robust COVID-19 Detection Using CT Images
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72. Dual-Attention Residual Network for Automatic Diagnosis of COVID-19
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74. PGUNeT: Covid-19 CT Image Segmentation Using GAN and Feature Pyramid
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75. Effect of Pre-processing of CT Images on the Performance of Deep Neural Networks Based Diagnosis of COVID-19
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76. ResidualCovid-Net: An Interpretable Deep Network to Screen COVID-19 Utilizing Chest CT Images
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77. Clinical Characteristics of COVID-19 Patients and Application to an Artificial Intelligence System for Disease Surveillance
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78. Interactive framework for Covid-19 detection and segmentation with feedback facility for dynamically improved accuracy and trust
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84. Multi-national COVID-19 CT Image-label Pairs Synthesis via Few-Shot GANs Adaptation
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85. Joint margin adaption and multiscale feature fusion for COVID-19 CT images segmentation
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86. A Customized 3D CNN Integrated with Convolutional Block Attention Module for Precise Diagnosis of COVID-19 and Pneumonia from CT Scan Images
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87. Assessing the Association between Biomarkers and COVID-19 Mortality Using the Joint Modelling Approach
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89. Adversarially Residual U$$^2$$Net for COVID-19 Lung Infection Segmentation from CT Images
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90. Survey on using deep learning to detection COVID-19 disease
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91. Automatic Clustering of CT Scans of COVID-19 Patients Based on Deep Learning
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92. Efficient Deep Neural Network for an Automated Detection of COVID-19 using CT images
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93. COVID-19 Severity Forecast Based on Machine Learning and Complete Blood Count Data
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94. Identification of images of COVID-19 from Chest Computed Tomography (CT) images using Deep learning: Comparing COGNEX VisionPro Deep Learning 1.0 Software with Open Source Convolutional Neural Networks
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95. Triple-view Convolutional Neural Networks for COVID-19 Diagnosis with Chest X-ray
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96. DABC-Net for robust pneumonia segmentation and prediction of COVID-19 progression on chest CT scans
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97. Predictors of Worsening Oxygenation in COVID-19
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99. Robust Automated Framework for COVID-19 Disease Identification from a Multicenter Dataset of Chest CT Scans.
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100. Hierarchical Automatic COVID-19 Detection via CT Scan Images
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