Automated quantification of SARS-CoV-2 pneumonia with large vision model knowledge adaptation

• Published in: New microbes and new infections Vol. 62; p. 101457
• Main Authors: Liang, Zhaohui, Xue, Zhiyun, Rajaraman, Sivaramakrishnan, Antani, Sameer
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.12.2024; Elsevier
• Subjects: (s) from the Special Issue on AI and Emerging Infections Edited by Jaffar A.Al-Tawfiq, Michel Bielecki, Thibault Lovey, Nadja Hedrich; Artificial intelligence; Large vision model; SARS-CoV2 pneumonia; Self-supervised learning; Vision transformer; Vision transformer; Artificial intelligence; SARS-CoV2 pneumonia; Large vision model; Self-supervised learning

Large vision models (LVM) pretrained by large datasets have demonstrated their enormous capacity to understand visual patterns and capture semantic information from images. We proposed a novel method of knowledge domain adaptation with pretrained LVM for a low-cost artificial intelligence (AI) model...