Diagnosis/Prognosis of COVID-19 Chest Images via Machine Learning and Hypersignal Processing: Challenges, opportunities, and applications
Arash Mohammadi, Yingxu Wang, Nastaran Enshaei, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Javad Rafiee, Helder C. R. Oliveira, Svetlana Yanushkevich, Konstantinos N. Plataniotis
Abstract
The novel coronavirus disease, COVID-19, has rapidly and abruptly changed the world as we knew it in 2020. It has become the most unprecedented challenge to analytic epidemiology (AE) in general and signal processing (SP) theories specifically. In this regard, medical imaging plays an important role for the management of COVID-19. SP and deep learning (DL) models can assist in the development of robust radiomics solutions for the diagnosis/prognosis, severity assessment, treatment response, and monitoring of COVID-19 patients.
Topics & Concepts
Coronavirus disease 2019 (COVID-19)RadiomicsEpidemiology2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Computer scienceArtificial intelligenceSignal processingMedical imagingMedicineIntensive care medicineMachine learningDiseaseRadiologyPathologyInfectious disease (medical specialty)Digital signal processingOutbreakComputer hardwareCOVID-19 diagnosis using AIRadiomics and Machine Learning in Medical ImagingAdvanced X-ray and CT Imaging