Development and Validation of an Early Scoring System for Prediction of Disease Severity in COVID-19 Using Complete Blood Count Parameters

<p>The coronavirus disease 2019 (COVID-19) after outbreaking in Wuhan increasingly spread throughout the world. Fast, reliable, and easily accessible clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce mortality. The objective of the s...

Full description

Saved in:

Bibliographic Details
Main Author:	Tawsifur Rahman (14150523) (author)
Other Authors:	Amith Khandakar (14151981) (author), Md Enamul Hoque (5807120) (author), Nabil Ibtehaz (16888773) (author), Saad Bin Kashem (16888776) (author), Reehum Masud (16888779) (author), Lutfunnahar Shampa (16888782) (author), Mohammad Mehedi Hasan (7326065) (author), Mohammad Tariqul Islam (7854059) (author), Somaya Al-Maadeed (5178131) (author), Susu M. Zughaier (14151987) (author), Saif Badran (16888785) (author), Suhail A. R. Doi (7490777) (author), Muhammad E. H. Chowdhury (14150526) (author)
Published:	2021
Subjects:	Biomedical and clinical sciences Cardiovascular medicine and haematology Health sciences Epidemiology Health services and systems Information and computing sciences Machine learning COVID-19 Hospitals Biomarkers Biological system modeling Pulmonary diseases Predictive models Complete blood count Prognostic model Early prediction of mortality risk Faculty of Robotics and Advanced Computing
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Development and Validation of an Early Scoring System for Prediction of Disease Severity in COVID-19 Using Complete Blood Count Parameters

Similar Items