COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

Background: The previous COVID-19 lung diagnosis system lacks both scientific validation and the role of explainable artificial intelligence (AI) for understanding lesion localization. This study presents a cloud-based explainable AI, the “COVLIAS 2.0-cXAI” system using four kinds of class activatio...

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Bibliographic Details
Main Authors: Jasjit S. Suri, Sushant Agarwal, Gian Luca Chabert, Alessandro Carriero, Alessio Paschè, Pietro S. C. Danna, Luca Saba, Armin Mehmedović, Gavino Faa, Inder M. Singh, Monika Turk, Paramjit S. Chadha, Amer M. Johri, Narendra N. Khanna, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Martin Miner, David W. Sobel, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanasios D. Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Jagjit S. Teji, Mustafa Al-Maini, Surinder K. Dhanjil, Andrew Nicolaides, Aditya Sharma, Vijay Rathore, Mostafa Fatemi, Azra Alizad, Pudukode R. Krishnan, Ferenc Nagy, Zoltan Ruzsa, Mostafa M. Fouda, Subbaram Naidu, Klaudija Viskovic, Mannudeep K. Kalra
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Diagnostics
Subjects:
COVID-19 lesion
lung CT
Hounsfield units
glass ground opacities
hybrid deep learning
explainable AI
Online Access:https://www.mdpi.com/2075-4418/12/6/1482

Internet

https://www.mdpi.com/2075-4418/12/6/1482

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