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Peer-Reviewed Publication
Proc SPIE Int Soc Opt Eng2024;12927February 1, 2024Journal Article

CAFES: Chest X-ray Analysis using Federated Self-supervised Learning for Pediatric COVID-19 Detection.

Abhijeet Parida1, Syed Muhammad Anwar1,2, Malhar P Patel3, Mathias Blom3, Tal Tiano Einat3, Alex Tonetti3, Yuval Baror3, Ittai Dayan3, Marius George Linguraru1,2
1Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, 111 Michigan Ave, Washington, DC 20010, USA.
2School of Medicine and Health Sciences, George Washington University, 2121 I St NW, Washington, DC 20052, USA.
3Rhino Health, 22 Boston Wharf Rd, MA 02210, USA.
PubMed PMC DOI PDF

Abstract

Chest X-rays (CXRs) play a pivotal role in cost-effective clinical assessment of various heart and lung related conditions. The urgency of COVID-19 diagnosis prompted their use in identifying conditions like lung opacity, pneumonia, and acute respiratory distress syndrome in pediatric patients. We propose an AI-driven solution for binary COVID-19 versus non-COVID-19 classification in pediatric CXR…

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