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Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis

arXiv 2003.05037 ↗First posted 10 Mar 2020eess.IV cs.CV cs.LGcited by 38

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Abstract (arXiv)

Purpose: Develop AI-based automated CT image analysis tools for detection, quantification, and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from non-patients. Materials and Methods: Multiple international datasets, including from Chinese disease-infected areas were included. We present a system that utilizes robust 2D and 3D deep learning models, modifying and adapting existing AI models and combining them with clinical understanding. We conducted multiple retrospective experiments to analyze the performance of the system in the detection of suspected COVID-19 thoracic CT features and to evaluate evolution of the disease in each patient over time using a 3D volume review, generating a Corona score. The study includes a testing set of 157 international patients (China and U.S). Results: Classification results for Coronavirus vs Non-coronavirus cases per thoracic CT studies were 0.996 AUC (95%CI: 0.989-1.00) ; on datasets of Chinese control and infected patients. Possible working point: 98.2% sensitivity, 92.2% specificity. For time analysis of Coronavirus patients, the system output enables quantitative measurements for smaller opacities (volume, diameter) and visualization of the larger opacities in a slice-based heat map or a 3D volume display. Our suggested Corona score measures the progression of disease over time. Conclusion: This initial study, which is currently being expanded to a larger population, demonstrated that rapidly developed AI-based image analysis can achieve high accuracy in detection of Coronavirus as well as quantification and tracking of disease burden.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Mar 2020.

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Citing papers per year: 2021: 19; 2022: 7; 2023: 8; 2024: 4.

38 papers.

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  1. 2021Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Datacited by 13
  2. 2022COVID-19 Detection and Analysis From Lung CT Images using Novel Channel Boosted CNNscited by 12
  3. 2021Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray imagescited by 10
  4. 2021The Prominence of Artificial Intelligence in COVID-19cited by 7
  5. 2021Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A reviewcited by 5
  6. 2024An Explainable Non-local Network for COVID-19 Diagnosiscited by 5
  7. 2024Navigating Distribution Shifts in Medical Image Analysis: A Surveycited by 5
  8. 2023COVID-19 Infection Analysis Framework using Novel Boosted CNNs and Radiological Imagescited by 4
  9. 2021Quadruple Augmented Pyramid Network for Multi-class COVID-19 Segmentation via CTcited by 3
  10. 2021Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Networkcited by 3
  11. 2021Semi-supervised Learning for COVID-19 Image Classification via ResNetcited by 2
  12. 2022L3-Net Deep Audio Embeddings to Improve COVID-19 Detection from Smartphone Datacited by 2
26 more
  1. 2023Performance of GAN-based augmentation for deep learning COVID-19 image classificationcited by 2
  2. 2021A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosiscited by 1
  3. 2021An Automated Approach for Timely Diagnosis and Prognosis of Coronavirus Diseasecited by 1
  4. 2021Systematic investigation into generalization of COVID-19 CT deep learning models with Gabor ensemble for lung involvement scoringcited by 1
  5. 2021CxSE: Chest X-ray Slow Encoding CNN forCOVID-19 Diagnosiscited by 1
  6. 2021Resetting the baseline: CT-based COVID-19 diagnosis with Deep Transfer Learning is not as accurate as widely thoughtcited by 1
  7. 2023COVID-19 Diagnosis: ULGFBP-ResNet51 approach on the CT and the Chest X-ray Images Classificationcited by 1
  8. 2021Explainability Guided Multi-Site COVID-19 CT Classificationcited by 0
  9. 2021DPN-SENet:A self-attention mechanism neural network for detection and diagnosis of COVID-19 from chest x-ray imagescited by 0
  10. 2021CoviLearn: A Machine Learning Integrated Smart X-Ray Device in Healthcare Cyber-Physical System for Automatic Initial Screening of COVID-19cited by 0
  11. 2021Understanding Human Innate Immune System Dependencies using Graph Neural Networkscited by 0
  12. 2021Machine Learning-Based COVID-19 Patients Triage Algorithm using Patient-Generated Health Data from Nationwide Multicenter Databasecited by 0
  13. 2021AI-Powered Semantic Segmentation and Fluid Volume Calculation of Lung CT images in Covid-19 Patientscited by 0
  14. 2021Detecting COVID-19 from Chest Computed Tomography Scans using AI-Driven Android Applicationcited by 0
  15. 2022Machine learning approaches for localized lockdown during COVID-19: a case study analysiscited by 0
  16. 2022A Deep Learning Approach for the Detection of COVID-19 from Chest X-Ray Images using Convolutional Neural Networkscited by 0
  17. 2022Prediction of COVID-19 using chest X-ray imagescited by 0
  18. 2022Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Imagecited by 0
  19. 2022Comparative Analysis of State-of-the-Art Deep Learning Models for Detecting COVID-19 Lung Infection from Chest X-Ray Imagescited by 0
  20. 2023Composite Deep Network with Feature Weighting for Improved Delineation of COVID Infection in Lung CTcited by 0
  21. 2023MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosiscited by 0
  22. 2023Transfer Learning for the Efficient Detection of COVID-19 from Smartphone Audio Datacited by 0
  23. 2023COVID-VR: A Deep Learning COVID-19 Classification Model Using Volume-Rendered Computer Tomographycited by 0
  24. 2023Cross-dataset domain adaptation for the classification COVID-19 using chest computed tomography imagescited by 0
  25. 2024Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classificationcited by 0
  26. 2024Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19cited by 0