Work

COVID-19 detection from Xray and CT scans using transfer learning

Year: 2021

Type: conference-paper

Abstract: Since the novel coronavirus SARS-CoV-2 outbreak, intensive research has been conducted to find suitable tools for diagnosis and identifying infected people in order to take appropriate action. Chest imaging plays a significant role in this phase where CT and Xrays scans have proven to be effective in detecting COVID-19 within the lungs. In this research, we propose deep learning models using Transfer learning to detect COVID-19. Both X-ray and CT scans were considered to evaluate the proposed methods.

Source: International Conference of Women in Data Science at Taif University (WiDSTaif)

DOI: 10.1109/widstaif52235.2021.9430229

Authors: Mohamed Berrimi, Skander Hamdi, Raoudha Yahia Cherif, Abdelouahab Moussaoui, Mourad Oussalah, Mafaza Chabane

Institutions: University Ferhat Abbas of Setif, University of Oulu

Language: English

Topic: COVID-19 diagnosis using AI

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

OpenAlex ID: W3172335971