Analyzing complex data linked to COVID-19 to support decision making and prognosis

This supplementary research project aims to propose, explore and develop new methods and algorithms to be used in decision-making processes for medical diagnosis and prognosis of patients in the context of COVID-19. These methods and algorithms will be instantiated in systems and applications that will be made available to the scientific community to support this decision-making process quickly and accurately. The challenges to be overcome begin with the assembly of databases and images from different and often incomplete platforms, and the application of the radiomic technique on X-ray (RX) and computed tomography (CT) images, with the premise of whereas massive quantitative and qualitative characteristics on X-ray images can bring the necessary information to the diagnosis of COVID-19, in the same way that CT provides. The advantage of this approach that will be investigated is the lower cost and greater availability of X-rays, allowing more patients to benefit from the results of this proposal. In addition to providing cured and consistent material for research and advances in the area of ​​COVID-19. In addition, consistent databases and images for research will be made available to the community in the area. (AU)