AI-for-COVID19: Predictive Diagnostics Platform Available to Global Scientific Community
This platform – “AIforCOVID Imaging Archive” enables the sharing of radiographic images from COVID-19 patients and development of leading-edge Artificial Intelligence-based methods for predicting clinical developments of the disease caused by SARS-CoV-2.
The platform has been promoted and implemented by Bracco Imaging with Centro Diagnostico Italiano, in partnership with major Italian hospitals and public and private research institutes.
The AIforCOVID Imaging Archive platform is on the EIBIR (European Institute for Biomedical Imaging Research) published list of Radiological Imaging databases which was conceived to foster the study and further development of Artificial Intelligence solutions applied to COVID-19 management.The platform was presented at the most recent European Congress of Radiology (ECR 2021) in Wien.
The shared collection of images and clinical data is used for developing innovative Artificial Intelligence-based methods to predict clinical developments of SARS-CoV-2-related disease. This valuable tool enables the international scientific community to share radiological and clinical data and find innovative solutions to combat the disease. The AIforCOVID Imaging Archive, is available, open access to the global scientific community and contains more than a thousand positive patient chest radiographic examinations carried out upon hospitalization. Each X-ray is associated with clinical information about the patient collected at that time.
Data was collected as part of the “AIforCOVID” no-profit multicentre research project, promoted by Bracco Imaging in partnership with the Centro Diagnostico Italiano. The initiative involved major hospitals and public/private research institutes in Italy.The Istituto Italiano di Tecnologia (IIT) of Genoa and Università Campus Bio-medico of Rome were responsible for data analysis and developed the artificial intelligence algorithms, working in partnership with the Centro Diagnostico Italiano and Bracco Imaging teams. These algorithms have the objective of identifying indicators of risk of a severe disease progression, providing physicians with a tool to evaluate the potential need for intensive therapy ahead of time.
Amazon Web Services was pivotal for the development of the platform. AWS supported the AIforCOVID project through the AWS Diagnostic Development Initiative, after recognizing it as one of the most innovative ongoing projects at international level. The platform integrates a range of AWS technologies, including machine learning and artificial intelligence from Amazon SageMaker, a fully managed service for creating, training and deploying machine learning models.
Prof. Lorenzo Preda, Director of the Radiology Department at the Ospedale San Matteo di Pavia, said: “Joint efforts between the San Matteo in Pavia and the other hospitals in the network coordinated by CDI-Bracco has, in a very short timeframe, made available input data acquired in the field for developing an extremely powerful AI system. The AIforCOVID Imaging Archive platform is another step in this sharing process.”
Michaela Cellina, a radiologist at Fatebenefratelli Sacco in Milan, says: “Throughout the COVID-19 pandemic, the role played by radiologists and radiological imaging techniques, particularly X-rays and CT, has been essential. Against the backdrop of our working conditions in 2020, with overcrowded emergency rooms and especially long processing times to get swab results back, radiological imaging proved to be a vital frontline tool for diagnosis and patient management. Because of the limited resources we had (and continue to have), with very few beds available for hospitalization, especially in intensive care, applying artificial intelligence tools capable of predicting patient outcomes from radiological examinations makes a real difference, enabling optimal management of patients and available resources. During this emergency, Italy’s radiologists have shown remarkable commitment. The development of multicentre studies and sharing data and direct clinical experience have markedly accelerated the development of effective weapons to fight this battle, one that we are still fighting.”
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