BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data

BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data

<p dir="ltr">Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge from the datasets collected from 930 COVID-19 pati...

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Bibliographic Details
Main Author: Tawsifur Rahman (14150523) (author)
Other Authors: Muhammad E. H. Chowdhury (14150526) (author), Amith Khandakar (14151981) (author), Zaid Bin Mahbub (16869975) (author), Md Sakib Abrar Hossain (17773173) (author), Abraham Alhatou (17773176) (author), Eynas Abdalla (17773179) (author), Sreekumar Muthiyal (17773182) (author), Khandaker Farzana Islam (17773185) (author), Saad Bin Abul Kashem (17773188) (author), Muhammad Salman Khan (7202543) (author), Susu M. Zughaier (14151987) (author), Maqsud Hossain (10675896) (author)
Published: 2023
Subjects:
Engineering
Biomedical engineering
Health sciences
Health services and systems
Information and computing sciences
Artificial intelligence
Machine learning
Multimodal system
COVID-19
Clinical data
Chest X-ray
Prognostic model
Deep learning
Classical machine learning
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