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AI-Driven quantification, staging and outcome prediction of COVID-19 pneumonia

Guillaume Chassagnon, Maria Vakalopoulou, Enzo Battistella, Stergios Christodoulidis, Trieu-Nghi Hoang-Thi, Severine Dangeard, Eric Deutsch, Fabrice Andre, Enora Guillo, Nara Halm, Stefany El Hajj, Florian Bompard (+23 others)
2020 Medical Image Analysis  
Our approach relies on automatic deep learning-based disease quantification using an ensemble of architectures, and a data-driven consensus for the staging and outcome prediction of the patients fusing  ...  In this study, we collected a multi-center cohort and we investigated the use of medical imaging and artificial intelligence for disease quantification, staging and outcome prediction.  ...  DIC20161236437), the Swiss National Science Foundation Grant no. 188153 and benefited from methodological developments done in the context of Dr.  ... 
doi:10.1016/ pmid:33171345 pmcid:PMC7558247 fatcat:iz5zcq7ftzg7lendm563asl7fu

AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia [article]

Guillaume Chassagnon, Maria Vakalopoulou, Enzo Battistella, Stergios Christodoulidis, Trieu-Nghi Hoang-Thi, Severine Dangeard, Eric Deutsch, Fabrice Andre, Enora Guillo, Nara Halm, Stefany El Hajj, Florian Bompard (+19 others)
2020 arXiv   pre-print
Chest computed tomography (CT) is widely used for the management of Coronavirus disease 2019 (COVID-19) pneumonia because of its availability and rapidity.  ...  The objective of this study is to address prediction of short-term outcomes, especially need for mechanical ventilation.  ...  Patients diagnosed with COVID-19 from March 4th to 29th at six large University Hospitals were eligible if they had positive PCR-RT and signs of COVID-19 pneumonia on unenhanced chest CT.  ... 
arXiv:2004.12852v1 fatcat:zrlolg4lpjb3tavvknncsa7jze

Automated AI-Driven CT Quantification of Lung Disease Predicts Adverse Outcomes in Patients Hospitalized for COVID-19 Pneumonia

Marie Laure Chabi, Ophélie Dana, Titouan Kennel, Alexia Gence-Breney, Hélène Salvator, Marie Christine Ballester, Marc Vasse, Anne Laure Brun, François Mellot, Philippe A. Grenier
2021 Diagnostics  
Automated quantification of lung disease at CT in COVID-19 pneumonia is useful to predict clinical deterioration or in-hospital death.  ...  or death in patients hospitalized with COVID-19 pneumonia. 323 consecutive patients (mean age 65 ± 15 years, 192 men), with laboratory-confirmed COVID-19 and an abnormal chest CT scan, were admitted to  ...  Acknowledgments: The authors thank Siemens Healthineers, and particularly Dorin Comaniciu, for providing the AI software for this study.  ... 
doi:10.3390/diagnostics11050878 pmid:34069115 pmcid:PMC8156322 fatcat:w5cmlnfdqnfgbdm6f65a4tz4v4

Artificial intelligence-based approaches for COVID-19 patient management

Lan Lan, Wenbo Sun, Dan Xu, Minhua Yu, Feng Xiao, Huijuan Hu, Haibo Xu, Xinghuan Wang
2021 Intelligent Medicine  
During the highly infectious pandemic of coronavirus disease 2019 (COVID-19), artificial intelligence (AI) has provided support in addressing challenges and accelerating achievements in controlling this  ...  In this paper, we specifically review the current status of AI-based approaches for patient management. Limitations and challenges still exist, and further needs are highlighted.  ...  Prognostic prediction Severity and adverse outcome prediction in the early stage of the disease is of great importance for risk stratification and allocation of intensive care medical resources, especially  ... 
doi:10.1016/j.imed.2021.05.005 pmid:34447600 pmcid:PMC8189732 fatcat:g6hj2jzvujc57ag55fualejxzy

Artificial Intelligence-Driven Assessment of Radiological Images for COVID-19

Yassine Bouchareb, Pegah Moradi Khaniabadi, Faiza Al Kindi, Humoud Al Dhuhli, Isaac Shiri, Habib Zaidi, Arman Rahmim
2021 Computers in Biology and Medicine  
Finally, the impact of AI and radiomics methods and the associated clinical outcomes are summarized.  ...  Artificial Intelligence (AI) methods have significant potential for diagnosis and prognosis of COVID-19 infections.  ...  Acknowledgements This work was supported by the Omani Research Council Grant, grant number RC/COVID-MED/RADI/20/01.  ... 
doi:10.1016/j.compbiomed.2021.104665 pmid:34343890 pmcid:PMC8291996 fatcat:nstm5p56rbgf5pd6hei42iia34

Factors associated with worsening oxygenation in patient with non-severe COVID-19 pneumonia

Cho Rom Hahm, Young Kyung Lee, Dong Hyun Oh, Mi Young Ahn, Jae-Phil Choi, Na Ree Kang, Jungkyun Oh, Hanzo Choi, Suhyun Kim
2021 Tuberculosis and Respiratory Diseases  
Our study presents initial CT evaluated by AI or visual severity scoring as well as serum markers of inflammation at admission are significantly associated with worsening oxygenation in this COVID-19 pneumonia  ...  This study aimed to determine parameters for worsening oxygenation in non-severe COVID-19 pneumonia.  ...  We used free software and found that the AI-driven parameters of pneumonia volume and extent of the whole lung in the initial chest CT predicted the worsening oxygenation in non-severe COVID-19 pneumonia  ... 
doi:10.4046/trd.2020.0139 pmid:33401345 pmcid:PMC8010417 fatcat:zibksz4lpbbzxoqwpehbcvgrqa

Would the Use of Artificial Intelligence in COVID-19 Patient Management Add Value to the Healthcare System?

Manuel Cossio, Ramiro E. Gilardino
2021 Frontiers in Medicine  
Dalia Dawood for her comments in the draft of this manuscript.  ...  To distinguish a normal LUS from COVID-19 pneumonia and other causes of pneumonia (bacterial, other viruses).  ...  images in four patterns: normal XR, potential COVID-19, and viral or bacterial pneumonia.  ... 
doi:10.3389/fmed.2021.619202 pmid:33585525 pmcid:PMC7873524 fatcat:l7zoxvijb5eyvi3weehlwhdtau

Applications of artificial intelligence in the thorax: a narrative review focusing on thoracic radiology

Yisak Kim, Ji Yoon Park, Eui Jin Hwang, Sang Min Lee, Chang Min Park
2021 Journal of Thoracic Disease  
COVID-19.  ...  reader, and the use of AI to facilitate complex quantifications.  ...  Figure 7 shows an example of an AI-assisted interpretation of CXR with COVID-19-associated pneumonia.  ... 
doi:10.21037/jtd-21-1342 pmid:35070379 pmcid:PMC8743417 fatcat:3fradsihgna35gow6fe3cehfxy

The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review

Maria Elena Laino, Angela Ammirabile, Alessandro Posa, Pierandrea Cancian, Sherif Shalaby, Victor Savevski, Emanuele Neri
2021 Diagnostics  
In this context, many recent studies have explored the role of AI in each of the presumed applications for COVID-19 infection chest imaging, suggesting that implementing AI applications for chest imaging  ...  Considering the ever expanding imaging data generated amid this pandemic, COVID-19 has catalyzed the rapid expansion in the application of AI to combat disease.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/diagnostics11081317 fatcat:prsewme7s5hojmb4rzk2sfgwa4

On the Role of Artificial Intelligence in Medical Imaging of COVID-19

Jannis Born, David Beymer, Deepta Rajan, Adam Coy, Vandana V Mukherjee, Matteo Manica, Prasanth Prasanna, Deddeh Ballah, Michal Guindy, Dorith Shaham, Pallav L Shah, Emmanouil Karteris (+3 others)
2021 Patterns  
We conducted the largest systematic review of the literature addressing the utility of AI in imaging for COVID-19 patient care.  ...  Although a plethora of research articles on AI methods on COVID-19 medical imaging are published, their clinical value remains unclear.  ...  quantification, staging and outcome prediction of COVID-19 pneumonia 29 prognosis, CT 2D/3D COVID- 19 quantification, roughly on par with radiologists.  ... 
doi:10.1016/j.patter.2021.100269 pmid:33969323 pmcid:PMC8086827 fatcat:p4xslz325ja55pmznupkcg7h5u

Holistic AI-Driven Quantification, Staging and Prognosis of COVID-19 Pneumonia [article]

Guillaume Chassagnon, Maria Vakalopoulou, Enzo Battistella, Stergios Christodoulidis, Trieu-Nghi Hoang-Thi, Severine Dangeard, Eric Deutsch, Fabrice Andre, Enora Guillo, Nara Halm, Stefany El Hajj, Florian Bompard (+23 others)
2020 medRxiv   pre-print
, and strong, reproducible staging/outcome prediction with good generalization properties using an ensemble of consensus methods.  ...  This approach relies on automatic computed tomography (CT)-based disease quantification using deep learning, robust data-driven identification of physiologically-inspired COVID-19 holistic patient profiling  ...  , staging and prognosis of COVID-19.  ... 
doi:10.1101/2020.04.17.20069187 fatcat:gq3burxzxnhxxg7dcg22vnj4du

Diagnosis/Prognosis of COVID-19 Images: Challenges, Opportunities, and Applications [article]

Arash Mohammadi, Yingxu Wang, Nastaran Enshaei, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Moezedin Javad Rafiee, Helder C. R. Oliveira, Svetlana Yanushkevich, Konstantinos N. Plataniotis
2020 arXiv   pre-print
SL/DL-based Radiomic models specific to the analysis of COVID-19 infection are then described covering the following four domains: Segmentation of COVID-19 lesions; Predictive models for outcome prediction  ...  and severity assessment) of COVID-19 infection.  ...  We would like to thank the consulting committee and EiC of IEEE SPM for their two-round reviews and encouraging comments.  ... 
arXiv:2012.14106v1 fatcat:5c52xdd3qneblfsjchtqwigzvu

Comparative Analysis of Covid-19 Classification and Detection Methodology

Rachi Jain
2020 International Journal for Research in Applied Science and Engineering Technology  
Coronavirus can spread by direct close contact or by coughing and sneezing of COVID-19 patients.  ...  COVID 19 spread very quickly, which is a leading cause of death and is responsible for approximately 7% of all deaths worldwide.  ...  In this paper, screening the COVID-19 is done in three stages. In the first stage AI model is trained to predict from a given CXR image the regions of interest, i.e., the mask of lung regions.  ... 
doi:10.22214/ijraset.2020.5178 fatcat:vbqdar3ntvaz5eql7jah736ml4

A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19

Tianming Wang, Zhu Chen, Quanliang Shang, Cong Ma, Xiangyu Chen, Enhua Xiao
2021 Diagnostics  
-19 research of disease diagnosis and classification, treatment decision-making, efficacy evaluation, and prognosis prediction.  ...  This review article describes the extensive research of medical image-based ML and AI methods in preventing and controlling COVID-19, and summarizes their characteristics, differences, and significance  ...  Acknowledgments: We would like to convey our greatest respects to the medical personnel who are fighting COVID-19.  ... 
doi:10.3390/diagnostics11101924 pmid:34679622 fatcat:yghmhfq7ircnjo6wpg7nluuziu

Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19

Danai Khemasuwan, Jeffrey S. Sorensen, Henri G. Colt
2020 European Respiratory Review  
Next, we review some of the literature relevant to the use of computer vision in medical imaging, predictive modelling with machine learning, and the use of AI for battling the novel severe acute respiratory  ...  First, we describe the concept of AI and some of the requisites of machine learning and deep learning.  ...  However, prediction models for COVID-19 may not always be accurate and reliable.  ... 
doi:10.1183/16000617.0181-2020 pmid:33004526 fatcat:3mn3hxfq6ncizhrfczbyo3vs6u
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